CA3038584A1

CA3038584A1 - Pupil tracking system and method, and digital display device and digital image rendering system and method using same

Info

Publication number: CA3038584A1
Application number: CA3038584A
Authority: CA
Inventors: Daniel Gotsch
Original assignee: Evolution Optiks Ltd
Current assignee: Evolution Optiks Ltd
Priority date: 2019-04-01
Filing date: 2019-04-01
Publication date: 2020-10-01
Also published as: CA3134669A1

Abstract

Described are various embodiments of a pupil tracking system and method, and digital display device and digital image rendering system and method using same.

Description

PUPIL TRACKING SYSTEM AND METHOD, AND DIGITAL DISPLAY DEVICE
AND DIGITAL IMAGE RENDERING SYSTEM AND METHOD USING SAME
FIELD OF THE DISCLOSURE
100011 The present disclosure relates to eye tracking and digital displays, and, in particular, to a pupil tracking system and method, and digital display device and digital image rendering system and method using same.
BACKGROUND

[0002] Gaze tracking technologies are currently being applied in different fields, for example, in the context of display content engagement tracking, or in tracking a user's attention and/or distraction in different contexts such as while driving a vehicle. One may generally define two broad categories of gaze tracking technologies. The first category generally relies on projecting near-IR light on a user's face and detecting corneo-scleral reflections (i.e. glints) on the user's eye to do so-called bright and/or dark pupil tracking.
Different products of this type are available, for example TOBII
(http://www.tobii.com) provides a range of products using such technology. Another broad category includes computer vision methods that rely on extracting facial features from digital images or videos. Examples of products for computer vision facial feature extraction include Face++ (https://www.faceplusplus.com) or the open source facial feature extraction library OpenFace (https://github.com/TadasBaltrusaitis/OpenFace).

[0003] Using these techniques, a user's gaze direction can be monitored in real-time and put in context to monitor what draw's the user's attention over time.

[0004] This background information is provided to reveal information believed by the applicant to be of possible relevance. No admission is necessarily intended, nor should be construed, that any of the preceding information constitutes prior art or forms part of the general common knowledge in the relevant art.
SUMMARY

[0005] The following presents a simplified summary of the general inventive concept(s) described herein to provide a basic understanding of some aspects of the disclosure. This summary is not an extensive overview of the disclosure. It is not intended to restrict key or critical elements of embodiments of the disclosure or to delineate their scope beyond that which is explicitly or implicitly described by the following description and claims.

[0006] In accordance with one aspect, there is provided a computer-implemented method, automatically implemented by one or more digital processors, for dynamically adjusting a digital image to be rendered on a digital display based on a corresponding viewer pupil location, the method comprising: sequentially acquiring a user pupil location; digitally computing from at least some said sequentially acquired user pupil location an estimated physical trajectory and/or velocity of said user pupil location over time; digitally predicting from said estimated physical trajectory and/or velocity a predicted user pupil location for a projected time; and digitally adjusting the digital image to be rendered at said projected time based on said predicted user pupil location.

[0007] In one embodiment, the said projected time is prior to a subsequent user pupil location acquisition.
100081 In one embodiment, the user pupil location is acquired at a given acquisition rate, and wherein the digital image is adjusted at an image refresh rate that is greater than said acquisition rate.
[0009] In one embodiment, the projecting is updated as a function of each new user pupil location acquisition.
[0010] In one embodiment, upon a latest user pupil location acquisition having been acquired within a designated time lapse, said adjusting is implemented based on said latest user pupil location acquisition, and whereas, upon said latest user pupil location acquisition having been acquired beyond said designated time lapse, said adjusting is implemented based on said projected user pupil location.

[0011] In one embodiment, the estimated trajectory is digitally predicted from a spline interpolation connecting said sequence of user pupil locations.
[0012] In one embodiment, the estimated trajectory is digitally predicted from a linear interpolation, a non-linear interpolation, or a non-parametric model of said sequence of user pupil locations.
[0013] In one embodiment, the digital display comprises a light field shaping layer (LFSL) through which the digital image is to be displayed, wherein said adjusting comprises adjusting pixel data based on said user pupil location to adjust a user perception of the digital image when viewed at said user pupil location through the LFSL.
[0014] In one embodiment, the adjusting comprises: digitally mapping the digital image on an adjusted image plane designated to provide the user with a designated image perception adjustment; associating adjusted image pixel data with at least some of said pixels according to said mapping; and rendering said adjusted image pixel data via said pixels thereby rendering a perceptively adjusted version of the digital image when viewed through said LFSL.
[0015] In one embodiment, the adjusted image plane is a virtual image plane virtually positioned relative to the digital display at a designated minimum viewing distance designated such that said perceptively adjusted version of the input image is adjusted to accommodate the viewer's reduced visual acuity.
[0016] In one embodiment, the adjusted image plane is designated as a user retinal plane, wherein said mapping is implemented by scaling the input image on said retinal plane as a function of an input user eye focus aberration parameter.
[0017] In one embodiment, the method further comprises digitally storing a time-ordered sequence of said user pupil location; wherein said estimated physical trajectory of said user pupil location over time is digitally computed from said time-ordered sequence.

[0018] In one embodiment, the method further comprises digitally computing an estimated pupil velocity and wherein said estimated physical trajectory is digitally computed based at least in part on said estimated pupil velocity.
[0019] In one embodiment, the estimated physical trajectory is computed via direct or indirect implementation of a predictive filter on at least some said sequentially acquired pupil location.
[0020] In accordance with another aspect, there is provided a computer-readable medium having instructions stored thereon to be automatically implemented by one or more processors to dynamically adjust a digital image to be rendered based on a 0 corresponding viewer pupil location by: sequentially acquiring a user pupil location;
digitally computing from at least some said sequentially acquired user pupil location an estimated physical trajectory and/or velocity of said user pupil location over time;
digitally predicting from said estimated trajectory and/or velocity a predicted user pupil location for a projected time; and digitally adjusting the digital image to be rendered at said projected time based on said predicted user pupil location.
[0021] In one embodiment, the projected time is prior to a subsequent user pupil location acquisition.
[0022] In one embodiment, the user pupil location is acquired at a given acquisition rate, and wherein the digital image is adjusted at an image refresh rate that is greater than said acquisition rate.
[0023] In one embodiment, the projecting is updated as a function of each new user pupil location acquisition.
[0024] In one embodiment, upon a latest user pupil location acquisition having been acquired within a designated time lapse, said adjusting is implemented based on said latest user pupil location acquisition, and whereas, upon said latest user pupil location acquisition having been acquired beyond said designated time lapse, said adjusting is implemented based on said projected user pupil location.

100251 In accordance with another aspect, there is provided a digital display device operable to automatically adjust a digital image to be rendered thereon, the device comprising: a digital display medium; a hardware processor; and a pupil tracking engine operable by said hardware processor to automatically: receive as input sequential user pupil locations; digitally compute from said sequential user pupil locations an estimated physical trajectory of said user pupil location over time; and digitally predict from said estimated trajectory a predicted user pupil location for a projected time;
wherein said hardware processor is operable to adjust the digital image to be rendered via said digital display medium at said projected time based on said predicted user pupil location.
[0026] In one embodiment, the pupil tracking engine is further operable to automatically acquire said sequential user pupil locations.
[0027] In one embodiment, the digital display device further comprises at least one camera, and wherein said pupil tracking engine is operable to interface with said at least one camera to acquire said user pupil locations.
[0028] In one embodiment, the digital display device further comprises at least one light source operable to illuminate said user pupil locations, wherein said pupil tracking engine is operable to interface with said at least one light source to acquire said user pupil locations.
[0029] In one embodiment, the at least one light source comprises an infrared or near infrared light source.
[0030] In one embodiment, the pupil tracking engine is operable to computationally locate said user pupil locations based on at least one of a machine vision process or a glint-based process.
[0031] In one embodiment, the device is operable to adjust a user perception of the digital image to be rendered thereon, the device further comprising: a light field shaping layer (LFSL) disposed relative to said digital display medium so to shape a light field emanating therefrom and thereby at least partially govern a projection thereof toward the user; wherein said hardware processor is operable to output adjusted image pixel data to be rendered via said digital display medium and projected through said LFSL so to produce a designated image perception adjustment when viewed from said predicted user pupil location.
[0032] Other aspects, features and/or advantages will become more apparent upon reading of the following non-restrictive description of specific embodiments thereof, given by way of example only with reference to the accompanying drawings.
BRIEF DESCRIPTION OF THE FIGURES
[0033] Several embodiments of the present disclosure will be provided, by way of examples only, with reference to the appended drawings, wherein:
[0034] Figure 1 is a schematic representation of a predicted pupil location calculated using a predictive pupil tracking process based on previously acquired pupil locations, according to one embodiment;
[0035] Figure 2 is schematic representation of a pupil location in three-dimensional space, according to one embodiment;
[0036] Figure 3 is a process flow diagram of a predictive pupil tracking method, according to one embodiment;
[0037] Figure 4 is a schematic representation of an effective pupil tracking frequency increased using a predictive pupil tracking process such as that sown in Figure 3, according to one embodiment;
[0038] Figure 5 is a schematic representation of an acquired pupil location sequence and a forecast pupil location predicted therefrom, according to one embodiment;
[0039] Figure 6 is a process flow diagram of an illustrative ray-tracing rendering process, in accordance with one embodiment;

[0040] Figures 7 and 8 are process flow diagrams of exemplary input constant parameters and variables, respectively, for the ray-tracing rendering process of Figure 6, in accordance with one embodiment;
[0041] Figures 9A to 9C are schematic diagrams illustrating certain process steps of Figure 6;
[0042] Figure 10 is process flow diagram of an illustrative ray-tracing rendering process, in accordance with another embodiment; and [0043] Figures 11 A to 11D are schematic diagrams illustrating certain process steps of Figure 10.
[0044] Elements in the several figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be emphasized relative to other elements for facilitating understanding of the various presently disclosed embodiments. Also, common, but well-understood elements that are useful or necessary in commercially feasible embodiments are often not depicted in order to facilitate a less obstructed view of these various embodiments of the present disclosure.
DETAILED DESCRIPTION
[0045] Various implementations and aspects of the specification will be described with reference to details discussed below. The following description and drawings are illustrative of the specification and are not to be construed as limiting the specification.
Numerous specific details are described to provide a thorough understanding of various implementations of the present specification. However, in certain instances, well-known or conventional details are not described in order to provide a concise discussion of implementations of the present specification.
[0046] Various apparatuses and processes will be described below to provide examples of implementations of the system disclosed herein. No implementation described below limits any claimed implementation and any claimed implementations may cover processes or apparatuses that differ from those described below. The claimed implementations are not limited to apparatuses or processes having all of the features of any one apparatus or process described below or to features common to multiple or all of the apparatuses or processes described below. It is possible that an apparatus or process described below is not an implementation of any claimed subject matter.
[0047] Furthermore, numerous specific details are set forth in order to provide a thorough understanding of the implementations described herein. However, it will be understood by those skilled in the relevant arts that the implementations described herein may be practiced without these specific details. In other instances, well-known methods, procedures and components have not been described in detail so as not to obscure the implementations described herein.
[0048] In this specification, elements may be described as "configured to" perform one or more functions or "configured for" such functions. In general, an element that is configured to perform or configured for performing a function is enabled to perform the function, or is suitable for performing the function, or is adapted to perform the function, or is operable to perform the function, or is otherwise capable of performing the function.
[0049] It is understood that for the purpose of this specification, language of "at least one of X, Y, and Z" and "one or more of X, Y and Z" may be construed as X
only, Y
only, Z only, or any combination of two or more items X, Y, and Z (e.g., XYZ, XY, YZ, ZZ, and the like). Similar logic may be applied for two or more items in any occurrence of "at least one ..." and "one or more..." language.
[0050] The systems and methods described herein provide, in accordance with different embodiments, different examples of a pupil tracking system and method, wherein one or more previously acquired pupil (center) locations can be used to generate and predict one or more future pupil (center) locations, thereby providing an increase in the effective rate of pupil tracking. In some embodiments, a digital display device and digital image rendering system and method are provided that rely, at least in part, on pupil tracking to adjust an output image thereof. For example, an image to be displayed can be adjusted, at least in part, as a function of a tracked user pupil location. In

8 accordance with some of the herein-described embodiments, an output image can therefore be adjusted not only as a function of an available user pupil location, but also or alternatively as a function a predicted user pupil location, for example, where an image refresh rate is higher than a pupil tracking rate.
[0051] For instance, while existing gaze tracking applications rely on real-time pupil location acquisitions to monitor a user's gaze direction in evaluating what is currently drawing their attention, such gaze tracking systems and methods are typically either insufficiently rapid or precise to support real-time applications requiring high resolution and high accuracy pupil location tracking. For example, the trade-off for operating real-time gaze trackers (e.g. trackers operating on a timescale in the order of roughly 100ms) is generally a low spatial accuracy, which may nonetheless suffice to monitor a general user gaze direction, whereas higher accuracy solutions will typically be much slower.
Accordingly, current solutions are not generally amenable to address applications where both a higher temporal resolution and spatial accuracy may be required, e.g.
where current gaze tracking solutions would generate prohibitive lag times and/or adversely impact a user experience.
[0052] For example, in some of the herein-described embodiments, a pupil tracking system and method is implemented for the purposes of applying adaptive image corrections or adjustments in a light field display system or device, whereby acquisition of a temporally accurate pupil location, in three-dimensions, is important in the delivery of a positive user experience. For example, certain embodiments involve the provision of corrective image rendering through light field shaping optics so to correct for a user's reduced visual acuity. An exemplary application for the herein-described embodiments is described in co-pending U.S. Patent Application serial No. 16/259,845 filed January 28, 2019 for a Light Field Display, Adjusted Pixel Rendering Method Therefor, and Vision Correction System and Method Using Same, the entire contents of which are hereby incorporated herein by reference. An example drawn therefrom is also described below, in accordance with one embodiment. In such embodiments, high pupil location accuracy may be required to ensure desired image corrections are adequately generated while minimizing the production of optical artefacts that may otherwise be distracting to the

9 viewer. Given the high spatial resolution required to implement such corrections, a high temporal sensitivity must also be addressed as slight displacements in the viewer's pupils may bring forth significant changes in ray tracing, or like vision correction computations, required to compute the various optical views provided through the light-field display and its impact on image correction and focused image rendering. As the viewer's eyes can readily perceive fluctuations within a temporal range of a few dozen milliseconds, a temporal pupil tracking resolution may be required in this order, in some embodiments, to ensure a quality user experience. Namely, pupil tracking outputs may be required on timescales similar to, or in the order of, an image refresh rate, so to ensure that .. appropriate image rendering is provided to provide the desired visual compensation without introducing adverse visual effects or delays.
[0053] Given the temporal constraints noted above, predictive pupil tracking is implemented, in accordance with some of the herein-described embodiments, so to mitigate delayed optical effects that may impact a viewer's experience and consequently provide for a better overall user experience.
[0054] With reference to Figure 1, and in accordance with one exemplary embodiment, a predictive pupil tracking system, generally referred to using the numeral 100, will now be described. In the illustrated embodiment of Figure 1, the system 100 relies on one or more pupil tracking devices or systems 105 to output a current pupil location. These may include, without limitation, any system using corneo-scleral reflections (i.e. glints) on the user's eye, from one or more IR or near-IR
light sources or the like (for either bright and/or dark pupil tracking); or computer vision-based methods using feature recognition applied to an image of the user's face obtained via a digital camera of the like.
[0055] Note that different devices using different technologies may be used in combination, for example, to leverage computation efficiencies in tracking and/or monitoring a user's eye and/or pupil location in different environments, and/or to provide metrics by which system accuracies can be evaluated, and different approaches weighted accordingly to provide higher overall system accuracies. Furthermore, different techniques may be implemented, for example, to reduce overall system power consumption, computational load, reduce hardware load requirements and/or reduce the viewer's exposure to various light probes (e.g. JR. Near-IR probes) typically used in glint-based pupil locating processes. For example, machine vision implementations may be relied upon at a first level to adequately locate and track facial features such as the user's eyes, pupils and pupil centers, whereas higher-resolution glint-based techniques may be layered thereon (e.g. via IRJNIR illumination) to refine and/or confirm machine vision results at a lower frequency, thus reducing IR/NIR emissions which may be unfavourable in certain conditions but may otherwise be required in other low lighting conditions. Similarly, different spatial estimation techniques may be applied to, again, reduce computational load by, for example, estimating pupil center locations using machine vision techniques by predominantly tracking eye locations (which are easier to track in general) and confirming pupil locations and/or centers at lower refresh rates.
These and other techniques may be considered herein without departing from the general .. scope and nature of the present disclosure.
[0056] With continued reference to Figure 1, generally, device(s) 105 is(are) operable to provide a sequence of pupil center positional data 109 of a user (e.g. 3D
position of the pupil center) in real-time or near real-time. For instance, where different techniques are used to computed pupil center locations 109, these different outputs may be combined, averaged and/or otherwise statistically compiled to produce pupil center location information useable in subsequent steps. For example, in some embodiments, a machine-vision based approach may be used to first estimate a location of the pupils.
This estimation may rely on various facial feature identification and/or extraction techniques, for example, but not limited to, by searching for and/or identifying the curvature of the .. eye(s), the dark pupil centers in contract with the sclera, etc., in combination, for example, with one or more glint-based techniques that, for example, may be constrained to previously machine-identified eye/pupil regions and/or be used a confirmation, validation or recalibration of such techniques. In some examples, past pupil locations may not only be used, directly or indirectly through one or more encoded variations or transformations thereof, to output predictive pupil location information, but also to seed pupil location measurements, for example, in the context of a machine vision pupil search algorithm or the like.
[0057] With continued reference to Figure 1, the system 100 uses, at least in part, data 109 as an input to a Prediction Engine 113 configured to analyze and generate therefrom one or more temporally predictive pupil locations 119 based on characteristic patterns automatically derived and interpreted from input data 109. For instance, one or more predicate data modeling techniques may be used by Prediction Engine 113 to extract one or more parameters representative of monitored real-time pupil location variation, and generate or construct therefrom a mathematical representation or model operable to output a predictive pupil locations 119. Some of these techniques will be discussed below, without limitation.
[0058] In some embodiments, one or more temporally predictive modeling methods (statistical or otherwise) can be used by Prediction Engine 113 to generate a predictive pupil location sequence 119. These may include, but are not limited to: moving averages, .. exponential smoothing, linear and/or non-linear regressions, spline interpolation, Box-Jenkins forecasting methods, Kalman Filters, alpha-beta filters, non-parametric models such as Gaussian Process Models and/or neural networks (including convolutional, recurrent or recursive neural networks). Generally, any amount of previously generated pupil location data, and/or data derived therefrom (e.g. velocity, acceleration, .. displacement trends or patterns, etc.) may be used in the estimation or extrapolation of the pupil center location to produce predictably reliable results. In some cases, a trajectory model (e.g. probable pupil location as a function time) from past data points may be extrapolated or projected beyond the last data point (pupil center location) to obtain an estimated trajectory (as a function of time) of (probable) future pupil locations.
.. Moreover, any number of estimated locations may be generated from the estimated trajectory while waiting for the next true pupil center location measurement, which can then be relied upon to refine the estimated trajectory and iteratively apply appropriate correction thereto to output ongoing predictive pupil location data.

[0059] In some embodiments, each pupil center location obtained from the pupil tracking device or system 105 may also comprise measurement errors associated therewith. These errors, if present, may be used by Prediction Engine 113 when generating the estimated pupil center sequence 113. The methods for incorporating such measurement errors in the modelling methods described above are well known in the art.
[0060] As shown in Figure 2, and in accordance with one embodiment, a pupil location is the three-dimensional position 212 of the pupil center 215 measured from a reference point 218. While the pupil moves slightly within the eye depending on where a user is focusing his/her gaze, the head and body of the user itself may move as well.
Within the context of a vision correction application, or other 3D lightfield image perception adjustment application, the pupil location in three dimensional space is generally set relative to a location of a light field display screen such that, in some embodiments, appropriate ray tracing processes can be implemented to at least partially govern how light emanated from each display pixel (of interest) is appropriately channeled through a corresponding light field shaping layer and relayed to the viewer's pupil. Naturally, as a viewer's pupil location changes relative to the display, so will corrective or otherwise adjusted pixel data change to adjust the output pixelated image accordingly. Accordingly, the light field display will generally include, or be associated with, related pupil tracking hardware such as one or more light sources (e.g.
IR/NIR) and/or cameras (visible, IR, NIR) and related pupil tracking firmware/software. Further details in respect of one illustrative embodiment will be described below.
[0061] With reference now to Figure 3, and in accordance with one exemplary embodiment, a predictive pupil tracking method using system 100 described above, and generally referred to using the numeral 300, will now be described. The above-described system 100 uses a sequence of pupil locations to generate predictive estimations of future pupil locations. As noted above, it will be appreciated that other direct, derived or transformed pupil location data may be used to this end. For simplicity, the following examples will focus on predictive trajectory models based on a time-ordered series of previously stored pupil locations.

[0062] The system described may thus be leveraged to complement or improve these pupil-tracking systems by generating one or more future pupil locations while another system or device is waiting for the eye or pupil tracking systems to acquire/compute a new location. Thus, the method described herein may provide for an improved frequency at which pupil locations are provided as output to another system or method.
For instance, output of a current pupil location may be delayed due to processing load and/or lag times, resulting in the output, in some applications, of somewhat stale data that, for example, when processed within the context of highly sensitive lightfield rendering applications (that will invariably introduce their own computational lag), result in the provision of a reduced viewer experience. Namely, an image rendered with the intent of providing a designated image perception for a given input pupil location may be unsatisfactorily rendered for the viewer if the viewer's pupil location changed significantly while image rendering computations were being implemented.
Accordingly, computational lag times, combined with the generally high refresh rates required to provide a enjoyable viewer experience, may introduce undesirable effects given at times noticeable pupil location changes. Using predictive pupil location data in light field rendering applications, as considered herein, may thus mitigate issues common with the use of otherwise stale static pupil location data.
[0063] Accordingly, the systems and methods described herein may be used to advantage in light field rendering methods or systems in which the pupil center position of a user is used to generate a light field image via a light field capable display or the like.
Indeed, the predictive pupil tracking method described herein, according to some embodiments, may make use of past pupil positional data to improve the speed or frequency at which the pupil center position, which is a moving target, is available to a light field ray tracing algorithm, or like light field rendering process.
Since the light field rendering embodiments described above rely, in part, on having an accurate pupil center location, the speed or frequency at which the pupil positional information is extracted by the pupil tracker may become a bottleneck for the light field rendering algorithm. A 60 Hz digital display (most phone displays for example) will have a refresh rate of about 15 ms, whereas higher frequency displays (e.g. 120Hz displays) have much faster refresh rates, which imposes significant constraints on the computation and output of accurate pupil tracking data, particularly when combined with computation loads involved in most light field rendering applications. For instance, for an optimal light field output experience, a rendered lightfield should be refreshed at or around the display screen's refresh rate. This refresh rate should naturally align with a current location of the user's pupil at that time and thus, benefits from a predictive pupil tracking approach that can extrapolate, from current data, where the pupil will actually be when the screen next refreshes to render a new lightfield output. Otherwise, the lack of temporal accuracy may lead to a reduced visual experience. Available computational power may thus be leveraged instead to predict or estimate, based on previous known (e.g.
measured) pupil center locations, an estimated future location of the pupil center and use this estimation to update the light field image while waiting for the next true pupil center location measurement, thereby resulting in a smoother viewing experience.
[0064] Coming back to Figure 3, a pupil location iterative refresh cycle is started at step 305. The method first checks at step 309 if, at this time, an actual measured pupil location is available from the one or more pupil tracking device or system 105. If this is the case, the method outputs the measured pupil location at step 313. If this is not the case, then at step 317, the method checks to see if enough prior pupil center locations (as measured by one or more pupil tracking device or system 105) have been recorded to provide enough data for prediction engine 113 to provide an accurate predicted one or more future pupil locations. If this is not the case, then the method goes back to step 305.
If enough data is available, then the method uses, at step 321, Prediction Engine 113 to generate the most probable trajectory (position as a function of time) of future pupil locations. It may then, at step 325, extract one or more future pupil locations from this trajectory, which are then fed back as output (step 313). The method loops back to step .. 305 once more. Therefore, the method as described above, always insures that measured pupil locations are outputted and used as soon as possible, while relying on Prediction Engine 113 to generate data points in between.
[0065] Similarly, predictive pupil tracking data can be used to accommodate predefined lightfield rendering lags, for example, where a pupil location is required early on in lightfield rendering computations (e.g. ray tracing) to output corrective or adaptive (016P-009-CA131 pixel data for rendering. Accordingly, rather than to compute ray traces, for example, on the basis of a current pupil location output, such computations may rely on a predictive location so that, when the corrected or adjusted image is finally computed and ready for display, the user's pupil is most likely now located at the predicted location and thus in an ideal location to best view the rendered image. These and other time lapse, lags and synchronization considerations may readily apply in different embodiments, as will be readily appreciated by the skilled artisan.
[0066] Figure 4 shows an exemplary schematic diagram relating a consecutive sequence of pupil location measurements with a corresponding time sequence (by a single unit of time for simplicity). Hence, the sequence from N to N+1 implies a time difference of one unit. Therefore, by using past pupil locations (N, N-1, N-2, etc.) to generate a most probable future pupil location at time T+1/2 (for example), the frequency at which pupil locations are available is effectively increased by a factor of two.
Likewise, a predictable pupil location may be forecasted when addressing higher computation load processes.
[0067] Figure 5 shows the positional change corresponding to the time sequence illustrated in Figure 4. The skilled technician will understand that the use of a 2D
representation is only for demonstration purposes and that an additional depth component can also normally be used. As explained above, each point (T-2, T-1 and T) represents a sequence of measured pupil center locations, separated in time. At time T, while waiting for the next measurement (the result of which will be available at time T+1), previous measurements (N, N-1, and N-2 from times T, T-1 and T-2 in this example) may be used to generate an estimated trajectory 515 of probable future pupil center location and extract therefrom an estimated future pupil location at time T+1/2.
EXAMPLE
[0068] The following example applies the predictive pupil tracking systems and methods described above within the context of an adjusted pixel rendering method used to produce an adjusted user image perception, for example, when applied to a light field display device. In some embodiments, the adjusted user image perception can accommodate, to some degree, a user's reduced visual acuity. To improve performance and accuracy, the user's pupil location, and changes therein, can be used as input, either via an integrated pupil tracking device and/or engine, or via interface with an external device and/or engine.
[0069] For instance, the devices, displays and methods described below may allow a user's perception of an input image to be displayed, to be adjusted or altered using the light field display as a function of the user's pupil location. For instance, in some examples, users who would otherwise require corrective eyewear such as glasses or contact lenses, or again bifocals, may consume images produced by such devices, displays and methods in clear or improved focus without the use of such eyewear. Other light field display applications, such as 3D displays and the like, may also benefit from the solutions described herein, and thus, should be considered to fall within the general scope and nature of the present disclosure.
[0070] For example, some of the herein described embodiments provide for digital display devices, or devices encompassing such displays, for use by users having reduced visual acuity, whereby images ultimately rendered by such devices can be dynamically processed to accommodate the user's reduced visual acuity so that they may consume rendered images without the use of corrective eyewear, as would otherwise be required.
As noted above, embodiments are not to be limited as such as the notions and solutions described herein may also be applied to other technologies in which a user's perception of an input image to be displayed can be altered or adjusted via the light field display.
[0071] Generally, digital displays as considered herein will comprise a set of image rendering pixels and a light field shaping layer disposed at a preset distance therefrom so to controllably shape or influence a light field emanating therefrom. For instance, each light field shaping layer will be defined by an array of optical elements centered over a corresponding subset of the display's pixel array to optically influence a light field emanating therefrom and thereby govern a projection thereof from the display medium toward the user, for instance, providing some control over how each pixel or pixel group will be viewed by the viewer's eye(s). As will be further detailed below, arrayed optical elements may include, but are not limited to, lenslets, microlenses or other such diffractive optical elements that together form, for example, a lenslet array;
pinholes or like apertures or windows that together form, for example, a parallax or like barrier;
concentrically patterned barriers, e.g. cut outs and/or windows, such as a to define a Fresnel zone plate or optical sieve, for example, and that together form a diffractive optical barrier (as described, for example, in Applicant's co-pending U.S.
Application Serial No. 15/910,908, the entire contents of which are hereby incorporated herein by reference); and/or a combination thereof, such as for example, a lenslet array whose respective lenses or lenslets are partially shadowed or barriered around a periphery thereof so to combine the refractive properties of the lenslet with some of the advantages provided by a pinhole barrier.
100721 In operation, the display device will also generally invoke a hardware processor operable on image pixel (or subpixel) data for an image to be displayed to output corrected or adjusted image pixel data to be rendered as a function of a stored characteristic of the light field shaping layer (e.g. layer distance from display screen, distance between optical elements (pitch), absolute relative location of each pixel or subpixel to a corresponding optical element, properties of the optical elements (size, diffractive and/or refractive properties, etc.), or other such properties, and a selected vision correction or adjustment parameter related to the user's reduced visual acuity or intended viewing experience. While light field display characteristics will generally remain static for a given implementation (i.e. a given shaping layer will be used and set for each device irrespective of the user), image processing can, in some embodiments, be dynamically adjusted as a function of the user's visual acuity or intended application so to actively adjust a distance of a virtual image plane, or perceived image on the user's retinal plane given a quantified user eye focus or like optical aberration(s), induced upon rendering the corrected/adjusted image pixel data via the static optical layer, for example, or otherwise actively adjust image processing parameters as may be considered, for example, when implementing a viewer-adaptive pre-filtering algorithm or like approach (e.g. compressive light field optimization), so to at least in part govern an image perceived by the user's eye(s) given pixel or subpixel-specific light visible thereby through the layer.

[0073] Accordingly, a given device may be adapted to compensate for different visual acuity levels and thus accommodate different users and/or uses. For instance, a particular device may be configured to implement and/or render an interactive graphical user interface (GUI) that incorporates a dynamic vision correction scaling function that dynamically adjusts one or more designated vision correction parameter(s) in real-time in response to a designated user interaction therewith via the GUI. For example, a dynamic vision correction scaling function may comprise a graphically rendered scaling function controlled by a (continuous or discrete) user slide motion or like operation, whereby the GUI can be configured to capture and translate a user's given slide motion operation to a corresponding adjustment to the designated vision correction parameter(s) scalable with a degree of the user's given slide motion operation. These and other examples are described in Applicant's co-pending U.S. Patent Application Serial No.
15/246,255, the entire contents of which are hereby incorporated herein by reference.
[0074] In general, a digital display device as considered herein may include, but is not limited to, smartphones, tablets, e-readers, watches, televisions, GPS
devices, laptops, desktop computer monitors, televisions, smart televisions, handheld video game consoles and controllers, vehicular dashboard and/or entertainment displays, ticketing or shopping kiosks, point-of-sale (POS) systems, workstations, or the like.
[0075] Generally, the device will comprise a processing unit, a digital display, and internal memory. The display can be an LCD screen, a monitor, a plasma display panel, an LED or OLED screen, or any other type of digital display defined by a set of pixels for rendering a pixelated image or other like media or information. Internal memory can be any form of electronic storage, including a disk drive, optical drive, read-only memory, random-access memory, or flash memory, to name a few examples. For illustrative purposes, memory has stored in it a vision correction or image adjustment application and/or a predictive pupil tracking engine, though various methods and techniques may be implemented to provide computer-readable code and instructions for execution by the processing unit in order to process pixel data for an image to be rendered in producing corrected pixel data amenable to producing a corrected image accommodating the user's reduced visual acuity (e.g. stored and executable image correction application, tool, utility or engine, etc.). Other components of the electronic device may optionally include, but are not limited to, one or more rear and/or front-facing camera(s) (e.g.
for onboard pupil tracking capabilities), pupil tracking light source, an accelerometer and/or other device positioning/orientation devices capable of determining the tilt and/or orientation of electronic device, or the like.
[0076] For example, the electronic device, or related environment (e.g.
within the context of a desktop workstation, vehicular console/dashboard, gaming or e-learning station, multimedia display room, etc.) may include further hardware, firmware and/or software components and/or modules to deliver complementary and/or cooperative features, functions and/or services. For example, as previously noted, a pupil/eye tracking system may be integrally or cooperatively implemented to improve or enhance corrective image rendering by tracking a location of the user's eye(s)/pupil(s) (e.g.
both or one, e.g.
dominant, eye(s)) and adjusting light field corrections accordingly. For instance, the device may include, integrated therein or interfacing therewith, one or more eye/pupil tracking light sources, such as one or more infrared (IR) or near-IR (NIR) light source(s) to accommodate operation in limited ambient light conditions, leverage retinal retro-reflections, invoke corneal reflection, and/or other such considerations. For instance, different IR/NIR pupil tracking techniques may employ one or more (e.g.
arrayed) directed or broad illumination light sources to stimulate retinal retro-reflection and/or corneal reflection in identifying and tracking a pupil location. Other techniques may employ ambient or IR/NIR light-based machine vision and facial recognition techniques to otherwise locate and track the user's eye(s)/pupil(s). To do so, one or more corresponding (e.g. visible, IR/NIR) cameras may be deployed to capture eye/pupil tracking signals that can be processed, using various image/sensor data processing techniques, to map a 3D location of the user's eye(s)/pupil(s). In the context of a mobile device, such as a mobile phone, such eye/pupil tracking hardware/software may be integral to the device, for instance, operating in concert with integrated components such as one or more front facing camera(s), onboard IR/NIR light source(s) and the like. In other user environments, such as in a vehicular environment, eye/pupil tracking hardware may be further distributed within the environment, such as dash, console, ceiling, windshield, mirror or similarly-mounted camera(s), light sources, etc.

100771 Furthermore, the electronic device in this example will comprise a light field shaping layer (LFSL) overlaid atop a display thereof and spaced therefrom (e.g. via an integrated or distinct spacer) or other such means as may be readily apparent to the skilled artisan. For the sake of illustration, the following examples will be described within the context of a light field shaping layer defined, at least in part, by a lenslet array comprising an array of microlenses (also interchangeably referred to herein as lenslets) that are each disposed at a distance from a corresponding subset of image rendering pixels in an underlying digital display. It will be appreciated that while a light field shaping layer may be manufactured and disposed as a digital screen overlay, other integrated concepts may also be considered, for example, where light field shaping elements are integrally formed or manufactured within a digital screen's integral components such as a textured or masked glass plate, beam-shaping light sources or like component. Accordingly, each lenslet will predictively shape light emanating from these pixel subsets to at least partially govern light rays being projected toward the user by the display device. As noted above, other light field shaping layers may also be considered herein without departing from the general scope and nature of the present disclosure, whereby light field shaping will be understood by the person of ordinary skill in the art to reference measures by which light, that would otherwise emanate indiscriminately (i.e.
isotropically) from each pixel group, is deliberately controlled to define predictable light rays that can be traced between the user and the device's pixels through the shaping layer.
100781 For greater clarity, a light field is generally defined as a vector function that describes the amount of light flowing in every direction through every point in space. In other words, anything that produces or reflects light has an associated light field. The embodiments described herein produce light fields from an object that are not "natural"
vector functions one would expect to observe from that object. This gives it the ability to emulate the "natural" light fields of objects that do not physically exist, such as a virtual display located far behind the light field display, which will be referred to now as the 'virtual image'. As noted in the examples below, in some embodiments, lightfield rendering may be adjusted to effectively generate a virtual image on a virtual image plane that is set at a designated distance from an input user pupil location, for example, so to effective push back, or move forward, a perceived image relative to the display device in accommodating a user's reduced visual acuity (e.g. minimum or maximum viewing distance). In yet other embodiments, lightfield rendering may rather or alternatively seek to map the input image on a retinal plane of the user, taking into account visual aberrations, so to adaptively adjust rendering of the input image on the display device to produce the mapped effect. Namely, where the unadjusted input image would otherwise typically come into focus in front of or behind the retinal plane (and/or be subject to other optical aberrations), this approach allows to map the intended image on the retinal plane and work therefrom to address designated optical aberrations accordingly.
Using this approach, the device may further computationally interpret and compute virtual image 1() distances tending toward infinity, for example, for extreme cases of presbyopia. This approach may also more readily allow, as will be appreciated by the below description, for adaptability to other visual aberrations that may not be as readily modeled using a virtual image and image plane implementation. In both of these examples, and like embodiments, the input image is digitally mapped to an adjusted image plane (e.g. virtual image plane or retinal plane) designated to provide the user with a designated image perception adjustment that at least partially addresses designated visual aberrations.
Naturally, while visual aberrations may be addressed using these approaches, other visual effects may also be implemented using similar techniques.
[0079] With reference to Figures 6 to 8, and in accordance with one embodiment, an exemplary, computationally implemented, ray-tracing method for rendering an adjusted image perception via a light field shaping layer (LFSL), for example a computationally corrected image that accommodates for the user's reduced visual acuity, will now be described. In this exemplary embodiment, a set of constant parameters 1102 may be pre-determined. These may include, for example, any data that are not expected to significantly change during a user's viewing session, for instance, which are generally based on the physical and functional characteristics of the display for which the method is to be implemented, as will be explained below. Similarly, every iteration of the rendering algorithm may use a set of input variables 1104 which are expected to change either at each rendering iteration or at least between each user's viewing session.

[0080] As illustrated in Figure 7, the list of constant parameters 1102 may include, without limitations, the distance 1204 between the display and the LFSL, the in-plane rotation angle 1206 between the display and LFSL frames of reference, the display resolution 1208, the size of each individual pixel 1210, the optical LFSL
geometry 1212, the size of each optical element 1214 within the LFSL and optionally the subpixel layout 1216 of the display. Moreover, both the display resolution 1208 and the size of each individual pixel 1210 may be used to pre-determine both the absolute size of the display in real units (i.e. in mm) and the three-dimensional position of each pixel within the display. In some embodiments where the subpixel layout 1216 is available, the position within the display of each subpixel may also be pre-determined. These three-dimensional location/positions are usually calculated using a given frame of reference located somewhere within the plane of the display, for example a corner or the middle of the display, although other reference points may be chosen. Concerning the optical layer geometry 1212, different geometries may be considered, for example a hexagonal geometry such as the one shown in Figure 8. Finally, by combining the distance 1204, the rotation angle 1206, and the geometry 1212 with the optical element size 1214, it is possible to similarly pre-determine the three-dimensional location/position of each optical element center with respect to the display's same frame of reference.
[0081] Figure 8, meanwhile, illustratively lists an exemplary set of input variables 1104 for method 1100, which may include any input data fed into method 1100 that may reasonably change during a user's single viewing session, and may thus include without limitation: the image(s) to be displayed 1306 (e.g. pixel data such as on/off, colour, brightness, etc.) and the minimum reading distance 1310 (e.g. one or more parameters representative of the user's reduced visual acuity or condition). In some embodiments, the eye depth 1314 may also be used.
[0082] The image data 1306, for example, may be representative of one or more digital images to be displayed with the digital pixel display. This image may generally be encoded in any data format used to store digital images known in the art. In some embodiments, images 1306 to be displayed may change at a given framerate.

[0083] Following from the above-described embodiments, a further input variable includes the three-dimensional pupil location 1308, and optional pupil size 1312. As detailed above, the input pupil location in this sequence may include a current pupil location as output from a corresponding pupil tracking system, or a predicted pupil location, for example, when the process 1100 is implemented at a higher refresh rate than that otherwise available from the pupil tracking system, for instance. As will be appreciated by the skilled artisan, the input pupil location 1308 may be provided by an external pupil tracking engine and/or devices 1305, or again provided by an internal engine and/or integrated devices, depending the application and implementation at hand.
For example, a self-contained digital display device such as a mobile phone, tablet, laptop computer, digital television, or the like may include integrated hardware to provide real time pupil tracking capabilities, such as an integrated camera and machine vision-based pupil tracking engine; integrated light source, camera and glint-based pupil tracking engine; and/or a combination thereof. In other embodiments or implementations, external pupil tracking hardware and/or firmware may be leveraged to provide a real time pupil location. For example, a vehicular dashboard, control or entertainment display may interface with an external camera(s) and/or pupil tracking hardware to produce a similar effect. Naturally, the integrated or distributed nature of the various hardware, firmware and/or software components required to execute the predictive pupil tracking functionalities described herein may vary for different applications, implementations and solution at hand.
[0084] The pupil location 1308, in one embodiment, is the three-dimensional coordinates of at least one the user's pupils' center with respect to a given reference frame, for example a point on the device or display. This pupil location 1308 may be derived from any eye/pupil tracking method known in the art. In some embodiments, the pupil location 1308 may be determined prior to any new iteration of the rendering algorithm, or in other cases, at a lower framerate. In some embodiments, only the pupil location of a single user's eye may be determined, for example the user's dominant eye (i.e. the one that is primarily relied upon by the user). In some embodiments, this position, and particularly the pupil distance to the screen may otherwise or additionally be rather approximated or adjusted based on other contextual or environmental parameters, such as an average or preset user distance to the screen (e.g.
typical reading distance for a given user or group of users; stored, set or adjustable driver distance in a vehicular environment; etc.).
[0085] In the illustrated embodiment, the minimum reading distance 1310 is defined as the minimal focus distance for reading that the user's eye(s) may be able to accommodate (i.e. able to view without discomfort). In some embodiments, different values of the minimum reading distance 1310 associated with different users may be entered, for example, as can other adaptive vision correction parameters be considered depending on the application at hand and vision correction being addressed.
[0086] With added reference to Figures 9A to 9C, once parameters 1102 and variables 1104 have been set, the method of Figure 11 then proceeds with step 1106, in which the minimum reading distance 1310 (and/or related parameters) is used to compute the position of a virtual (adjusted) image plane 1405 with respect to the device's display, followed by step 1108 wherein the size of image 1306 is scaled within the image plane .. 1405 to ensure that it correctly fills the pixel display 1401 when viewed by the distant user. This is illustrated in Figure 14A, which shows a diagram of the relative positioning of the user's pupil 1415, the light field shaping layer 1403, the pixel display 1401 and the virtual image plane 1405. In this example, the size of image 1306 in image plane 1405 is increased to avoid having the image as perceived by the user appear smaller than the display's size.
100871 An exemplary ray-tracing methodology is described in steps 1110 to 1128 of Figure 6, at the end of which the output color of each pixel of pixel display 1401 is known so as to virtually reproduce the light field emanating from an image positioned at the virtual image plane 1405. In Figure 6, these steps are illustrated in a loop over each pixel in pixel display 1401, so that each of steps 1110 to 1126 describes the computations done for each individual pixel. However, in some embodiments, these computations need not be executed sequentially, but rather, steps 1110 to 1128 may executed in parallel for each pixel or a subset of pixels at the same time.
Indeed, as will be discussed below, this exemplary method is well suited to vectorization and implementation on highly parallel processing architectures such as GPUs.
[0088] As illustrated in Figure 14A, in step 1110, for a given pixel 1409 in pixel display 1401, a trial vector 1413 is first generated from the pixel's position to the (actual or predicted) center position 1417 of pupil 1415. This is followed in step 1112 by calculating the intersection point 1411 of vector 1413 with the LFSL 1403.
[0089] The method then finds, in step 1114, the coordinates of the center 1416 of the LFSL optical element closest to intersection point 1411. Once the position of the center 1416 of the optical element is known, in step 1116, a normalized unit ray vector is generated from drawing and normalizing a vector 1423 drawn from center position 1416 to pixel 1409. This unit ray vector generally approximates the direction of the light field emanating from pixel 1409 through this particular light field element, for instance, when considering a parallax barrier aperture or lenslet array (i.e. where the path of light travelling through the center of a given lenslet is not deviated by this lenslet). Further computation may be required when addressing more complex light shaping elements, as will be appreciated by the skilled artisan. The direction of this ray vector will be used to find the portion of image 1306, and thus the associated color, represented by pixel 1409.
But first, in step 1118, this ray vector is projected backwards to the plane of pupil 1415, and then in step 1120, the method verifies that the projected ray vector 1425 is still within pupil 1415 (i.e. that the user can still "see" it). Once the intersection position, for example location 1431 in Figure 14B, of projected ray vector 1425 with the pupil plane is known, the distance between the pupil center 1417 and the intersection point 1431 may be calculated to determine if the deviation is acceptable, for example by using a pre-determined pupil size and verifying how far the projected ray vector is from the pupil center.
[0090] If this deviation is deemed to be too large (i.e. light emanating from pixel 1409 channeled through optical element 1416 is not perceived by pupil 1415), then in step 1122, the method flags pixel 1409 as unnecessary and to simply be turned off or render a black color. Otherwise, as shown in Figure 14C, in step 1124, the ray vector is projected once more towards virtual image plane 1405 to find the position of the intersection point 1423 on image 1306. Then in step 1126, pixel 1409 is flagged as having the color value associated with the portion of image 1306 at intersection point 1423.
[0091] In some embodiments, method 1100 is modified so that at step 1120, instead of having a binary choice between the ray vector hitting the pupil or not, one or more smooth interpolation function (i.e. linear interpolation, Hermite interpolation or similar) are used to quantify how far or how close the intersection point 1431 is to the pupil center 1417 by outputting a corresponding continuous value between 1 or 0. For example, the assigned value is equal to 1 substantially close to pupil center 1417 and gradually change to 0 as the intersection point 1431 substantially approaches the pupil edges or beyond. In this case, the branch containing step 1122 is ignored and step 1220 continues to step 1124. At step 1126, the pixel color value assigned to pixel 1409 is chosen to be somewhere between the full color value of the portion of image 1306 at intersection point .. 1423 or black, depending on the value of the interpolation function used at step 1120 (1 or 0).
[0092] In yet other embodiments, pixels found to illuminate a designated area around the pupil may still be rendered, for example, to produce a buffer zone to accommodate small movements in pupil location, for example, or again, to address potential .. inaccuracies, misalignments or to create a better user experience.
100931 In some embodiments, steps 1118, 1120 and 1122 may be avoided completely, the method instead going directly from step 1116 to step 1124. In such an exemplary embodiment, no check is made that the ray vector hits the pupil or not, but instead the method assumes that it always does.
[0094] Once the output colors of all pixels have been determined, these are finally rendered in step 1130 by pixel display 1401 to be viewed by the user, therefore presenting a light field corrected image. In the case of a single static image, the method may stop here. However, new input variables may be entered and the image may be refreshed at any desired frequency, for example because the user's pupil moves as a function of time and/or because instead of a single image a series of images are displayed at a given framerate.
[0095] With reference to Figures 10 and 11 A to 11D, and in accordance with one embodiment, another exemplary computationally implemented ray-tracing method for rendering an adjusted image via the light field shaping layer (LFSL) that accommodates for the user's reduced visual acuity, for example, will now be described. In this embodiment, the adjusted image portion associated with a given pixel/subpixel is computed (mapped) on the retina plane instead of the virtual image plane considered in the above example, again in order to provide the user with a designated image perception to adjustment. Therefore, the currently discussed exemplary embodiment shares some steps with the method of Figure 6. Indeed, a set of constant parameters 1402 may also be pre-determined. These may include, for example, any data that are not expected to significantly change during a user's viewing session, for instance, which are generally based on the physical and functional characteristics of the display for which the method is to be implemented, as will be explained below. Similarly, every iteration of the rendering algorithm may use a set of input variables 1404 which are expected to change either at each rendering iteration or at least between each user viewing session. The list of possible variables and constants is substantially the same as the one disclosed in Figures 7 and 8 and will thus not be replicated here.
[0096] Once parameters 1402 and variables 1404 have been set, this second exemplary ray-tracing methodology proceeds from steps 1910 to 1936, at the end of which the output color of each pixel of the pixel display is known so as to virtually reproduce the light field emanating from an image perceived to be positioned at the correct or adjusted image distance, in one example, so to allow the user to properly focus on this adjusted image (i.e. having a focused image projected on the user's retina) despite a quantified visual aberration. In Figure 10, these steps are illustrated in a loop over each pixel in pixel display 1401, so that each of steps 1910 to 1934 describes the computations done for each individual pixel. However, in some embodiments, these computations need not be executed sequentially, but rather, steps 1910 to 1934 may be executed in parallel for each pixel or a subset of pixels at the same time. Indeed, as will be discussed below, this second exemplary method is also well suited to vectorization and implementation on highly parallel processing architectures such as GPUs.
[0097] Referencing once more Figure 9A, in step 1910 (as in step 1110), for a given pixel in pixel display 1401, a trial vector 1413 is first generated from the pixel's position to (actual or predicted) pupil center 1417 of the user's pupil 1415. This is followed in step 1912 by calculating the intersection point of vector 1413 with optical layer 1403.
[0098] From there, in step 1914, the coordinates of the optical element center 1416 closest to intersection point 1411 are determined. This step may be computationally intensive and will be discussed in more depth below. As shown in Figure 9B, once the position of the optical element center 1416 is known, in step 1916, a normalized unit ray vector is generated from drawing and normalizing a vector 1423 drawn from optical element center 1416 to pixel 1409. This unit ray vector generally approximates the direction of the light field emanating from pixel 1409 through this particular light field element, for instance, when considering a parallax barrier aperture or lenslet array (i.e.
where the path of light travelling through the center of a given lenslet is not deviated by this lenslet). Further computation may be required when addressing more complex light shaping elements, as will be appreciated by the skilled artisan. In step 1918, this ray vector is projected backwards to pupil 1415, and then in step 1920, the method ensures that the projected ray vector 1425 is still within pupil 1415 (i.e. that the user can still "see" it). Once the intersection position, for example location 1431 in Figure 14B, of projected ray vector 1425 with the pupil plane is known, the distance between the pupil center 1417 and the intersection point 1431 may be calculated to determine if the deviation is acceptable, for example by using a pre-determined pupil size and verifying how far the projected ray vector is from the pupil center.
[0099] Now referring to Figures 11A to 11D, steps 1921 to 1929 of method 1900 will be described. Once optical element center 1416 of the relevant optical unit has been determined, at step 1921, a vector 2004 is drawn from optical element center 1416 to (actual or predicted) pupil center 1417. Then, in step 1923, vector 2004 is projected further behind the pupil plane onto (microlens or MLA) focal plane 2006 (location where any light rays originating from optical layer 1403 would be focused by the eye's lens) to locate focus point 2008. For a user with perfect vision, focal plane 2006 would be located at the same location as retina plane 2010, but in this example, focal plane 2006 is located behind retina plane 2006, which would be expected for a user with some form of farsightedness. The position of focal plane 2006 may be derived from the user's minimum reading distance 1310, for example, by deriving therefrom the focal length of the user's eye. Other manually input or computationally or dynamically adjustable means may also or alternatively considered to quantify this parameter.
[00100] The skilled artisan will note that any light ray originating from optical element center 1416, no matter its orientation, will also be focused onto focus point 2008, to a first approximation. Therefore, the location on retina plane (2012) onto which light entering the pupil at intersection point 1431 will converge may be approximated by drawing a straight line between intersection point 1431 where ray vector 1425 hits the pupil 1415 and focus point 2008 on focal plane 2006. The intersection of this line with retina plane 2010 (retina image point 2012) is thus the location on the user's retina corresponding to the image portion that will be reproduced by corresponding pixel 1409 as perceived by the user. Therefore, by comparing the relative position of retina point 2012 with the overall position of the projected image on the retina plane 2010, the relevant adjusted image portion associated with pixel 1409 may be computed.
.. [00101] To do so, at step 1927, the corresponding projected image center position on retina plane 2010 is calculated. Vector 2016 is generated originating from the center position of display 1401 (display center position 2018) and passing through pupil center 1417. Vector 2016 is projected beyond the pupil plane onto retina plane 2010, wherein the associated intersection point gives the location of the corresponding retina image center 2020 on retina plane 2010. The skilled technician will understand that step 1927 could be performed at any moment prior to step 1929, once the relative pupil center location 1417 is known in input variables step 1904. Once image center 2020 is known, one can then find the corresponding image portion of the selected pixel/subpixel at step 1929 by calculating the x/y coordinates of retina image point 2012 relative to retina image center 2020 on the retina, scaled to the x/y retina image size 2031.

[00102] This retina image size 2031 may be computed by calculating the magnification of an individual pixel on retina plane 2010, for example, which may be approximately equal to the x or y dimension of an individual pixel multiplied by the eye depth 1314 and divided by the absolute value of the distance to the eye (i.e.
the magnification of pixel image size from the eye lens). Similarly, for comparison purposes, the input image is also scaled by the image ?ay dimensions to produce a corresponding scaled input image 2064. Both the scaled input image and scaled retina image should have a width and height between -0.5 to 0.5 units, enabling a direct comparison between a point on the scaled retina image 2010 and the corresponding scaled input image 2064, as shown in Figure 20D.
[00103] From there, the image portion position 2041 relative to retina image center position 2043 in the scaled coordinates (scaled input image 2064) corresponds to the inverse (because the image on the retina is inverted) scaled coordinates of retina image point 2012 with respect to retina image center 2020. The associated color with image portion position 2041 is therefrom extracted and associated with pixel 1409.
[00104] In some embodiments, method 1900 may be modified so that at step 1920, instead of having a binary choice between the ray vector hitting the pupil or not, one or more smooth interpolation function (i.e. linear interpolation, Hermite interpolation or similar) are used to quantify how far or how close the intersection point 1431 is to the pupil center 1417 by outputting a corresponding continuous value between 1 or 0. For example, the assigned value is equal to 1 substantially close to pupil center 1417 and gradually change to 0 as the intersection point 1431 substantially approaches the pupil edges or beyond. In this case, the branch containing step 1122 is ignored and step 1920 continues to step 1124. At step 1931, the pixel color value assigned to pixel 1409 is chosen to be somewhere between the full color value of the portion of image 1306 at intersection point 1423 or black, depending on the value of the interpolation function used at step 1920 (1 or 0).
[00105] In yet other embodiments, pixels found to illuminate a designated area around the pupil may still be rendered, for example, to produce a buffer zone to accommodate small movements in pupil location, for example, or again, to address potential inaccuracies or misalignments.
[00106] Once the output colors of all pixels in the display have been determined (check at step 1934 is true), these are finally rendered in step 1936 by pixel display 1401 to be viewed by the user, therefore presenting a light field corrected image.
In the case of a single static image, the method may stop here. However, new input variables may be entered and the image may be refreshed at any desired frequency, for example because the user's pupil moves as a function of time and/or because instead of a single image a series of images are displayed at a given framerate.
[00107] As will be appreciated by the skilled artisan, selection of the adjusted image plane onto which to map the input image in order to adjust a user perception of this input image allows for different ray tracing approaches to solving a similar challenge, that is of creating an adjusted image using the light field display that can provide an adjusted user perception, such as addressing a user's reduce visual acuity. While mapping the input image to a virtual image plane set at a designated minimum (or maximum) comfortable viewing distance can provide one solution, the alternate solution may allow accommodation of different or possibly more extreme visual aberrations. For example, where a virtual image is ideally pushed to infinity (or effectively so), computation of an infinite distance becomes problematic. However, by designating the adjusted image plane as the retinal plane, the illustrative process of Figure 10 can accommodate the formation of a virtual image effectively set at infinity without invoking such computational challenges. Likewise, while first order focal length aberrations are illustratively described with reference to Figure 10, higher order or other optical anomalies may be considered within the present context, whereby a desired retinal image is mapped out and traced while accounting for the user's optical aberration(s) so to compute adjusted pixel data to be rendered in producing that image. These and other such considerations should be readily apparent to the skilled artisan.
[00108] While the computations involved in the above described ray-tracing algorithms (steps 1110 to 1128 of Figure 6 or steps 1920 to 1934 of Figure 10) may be

10 I 6P-009-CAD I

done on general CPUs, it may be advantageous to use highly parallel programming schemes to speed up such computations. While in some embodiments, standard parallel programming libraries such as Message Passing Interface (MF1) or OPENMP may be used to accelerate the light field rendering via a general-purpose CPU, the light field computations described above are especially tailored to take advantage of graphical processing units (GPU), which are specifically tailored for massively parallel computations. Indeed, modern GPU chips are characterized by the very large number of processing cores, and an instruction set that is commonly optimized for graphics. In typical use, each core is dedicated to a small neighborhood of pixel values within an image, e.g., to perform processing that applies a visual effect, such as shading, fog, affine transformation, etc. GPUs are usually also optimized to accelerate exchange of image data between such processing cores and associated memory, such as RGB frame buffers.
Furthermore, smartphones are increasingly being equipped with powerful GPUs to speed the rendering of complex screen displays, e.g., for gaming, video, and other image-intensive applications. Several programming frameworks and languages tailored for programming on GPUs include, but are not limited to, CUDA, OpenCL, OpenGL
Shader Language (GLSL), High-Level Shader Language (HLSL) or similar. However, using GPUs efficiently may be challenging and thus require creative steps to leverage their capabilities, as will be discussed below.
[00109] While the present disclosure describes various embodiments for illustrative purposes, such description is not intended to be limited to such embodiments.
On the contrary, the applicant's teachings described and illustrated herein encompass various alternatives, modifications, and equivalents, without departing from the embodiments, the general scope of which is defined in the appended claims. Except to the extent necessary or inherent in the processes themselves, no particular order to steps or stages of methods or processes described in this disclosure is intended or implied. In many cases the order of process steps may be varied without changing the purpose, effect, or import of the methods described.
[00110] Information as herein shown and described in detail is fully capable of attaining the above-described object of the present disclosure, the presently preferred embodiment of the present disclosure, and is, thus, representative of the subject matter which is broadly contemplated by the present disclosure. The scope of the present disclosure fully encompasses other embodiments which may become apparent to those skilled in the art, and is to be limited, accordingly, by nothing other than the appended claims, wherein any reference to an element being made in the singular is not intended to mean "one and only one" unless explicitly so stated, but rather "one or more." All structural and functional equivalents to the elements of the above-described preferred embodiment and additional embodiments as regarded by those of ordinary skill in the art are hereby expressly incorporated by reference and are intended to be encompassed by to the present claims. Moreover, no requirement exists for a system or method to address each and every problem sought to be resolved by the present disclosure, for such to be encompassed by the present claims. Furthermore, no element, component, or method step in the present disclosure is intended to be dedicated to the public regardless of whether the element, component, or method step is explicitly recited in the claims.
However, that various changes and modifications in form, material, work-piece, and fabrication material detail may be made, without departing from the spirit and scope of the present disclosure, as set forth in the appended claims, as may be apparent to those of ordinary skill in the art, are also encompassed by the disclosure.

loi 6P-009-CAD I

Claims

What is claimed is:

1. A computer-implemented method, automatically implemented by one or more digital processors, for dynamically adjusting a digital image to be rendered on a digital display based on a corresponding viewer pupil location, the method comprising:
sequentially acquiring a user pupil location;
digitally computing from at least some said sequentially acquired user pupil location an estimated physical trajectory and/or velocity of said user pupil location over time;
digitally predicting from said estimated physical trajectory and/or velocity a predicted user pupil location for a projected time; and digitally adjusting the digital image to be rendered at said projected time based on said predicted user pupil location.

2. The computer-implemented method of claim 1, wherein said projected time is prior to a subsequent user pupil location acquisition.

3. The computer-implemented method of claim 1 or claim 2, wherein said user pupil location is acquired at a given acquisition rate, and wherein the digital image is adjusted at an image refresh rate that is greater than said acquisition rate.

4. The computer-implemented method of any one of claims 1 to 3, wherein said projecting is updated as a function of each new user pupil location acquisition.

5. The computer-implemented method of any one of claims 1 to 4, wherein, upon a latest user pupil location acquisition having been acquired within a designated time lapse, said adjusting is implemented based on said latest user pupil location acquisition, and whereas, upon said latest user pupil location acquisition having been acquired beyond said designated time lapse, said adjusting is implemented based on said projected user pupil location.

6. The computer-implemented method of any one of claims 1 to 5, wherein said estimated trajectory is digitally predicted from a spline interpolation connecting said sequence of user pupil locations.

7. The computer-implemented method of any one of claims 1 to 5, wherein said estimated trajectory is digitally predicted from a linear interpolation, a non-linear interpolation, or a non-parametric model of said sequence of user pupil locations.

8. The computer-implemented method of any one of claims 1 to 7, wherein the digital display comprises a light field shaping layer (LFSL) through which the digital image is to be displayed, wherein said adjusting comprises adjusting pixel data based on said user pupil location to adjust a user perception of the digital image when viewed at said user pupil location through the LFSL.

9. The computer-implemented method of claim 8, wherein said adjusting comprises:
digitally mapping the digital image on an adjusted image plane designated to provide the user with a designated image perception adjustment;
associating adjusted image pixel data with at least some of said pixels according to said mapping; and rendering said adjusted image pixel data via said pixels thereby rendering a perceptively adjusted version of the digital image when viewed through said LFSL.

10. The computer-implemented method of claim 9, wherein said adjusted image plane is a virtual image plane virtually positioned relative to the digital display at a designated minimum viewing distance designated such that said perceptively adjusted version of the input image is adjusted to accommodate the viewer's reduced visual acuity.

11. The computer-implemented method of claim 9, wherein said adjusted image plane is designated as a user retinal plane, wherein said mapping is implemented by scaling the input image on said retinal plane as a function of an input user eye focus aberration parameter.

12. The computer-implemented method of any one of claims 1 to 11, further comprising digitally storing a time-ordered sequence of said user pupil location; wherein said estimated physical trajectory of said user pupil location over time is digitally computed from said time-ordered sequence.

13. The computer-implemented method of any one of claims 1 to 12, further comprising digitally computing an estimated pupil velocity and wherein said estimated physical trajectory is digitally computed based at least in part on said estimated pupil velocity.

14. The computer-implemented method of claim 1, wherein said estimated physical trajectory is computed via direct or indirect implementation of a predictive filter on at least some said sequentially acquired pupil location.

15. A computer-readable medium having instructions stored thereon to be automatically implemented by one or more processors to dynamically adjust a digital image to be rendered based on a corresponding viewer pupil location by:
sequentially acquiring a user pupil location;
digitally computing from at least some said sequentially acquired user pupil location an estimated physical trajectory and/or velocity of said user pupil location over time;
digitally predicting from said estimated trajectory and/or velocity a predicted user pupil location for a projected time; and digitally adjusting the digital image to be rendered at said projected time based on said predicted user pupil location.

16. The computer-readable medium of claim 15, wherein said projected time is prior to a subsequent user pupil location acquisition.

17. The computer-readable medium of claim 15 or claim 16, wherein said user pupil location is acquired at a given acquisition rate, and wherein the digital image is adjusted at an image refresh rate that is greater than said acquisition rate.

18. The computer-readable medium of any one of claims 15 to 17, wherein said projecting is updated as a function of each new user pupil location acquisition.

19. The computer-readable medium of any one of claims 15 to 18, wherein, upon a latest user pupil location acquisition having been acquired within a designated time lapse, said adjusting is implemented based on said latest user pupil location acquisition, and whereas, upon said latest user pupil location acquisition having been acquired beyond said designated time lapse, said adjusting is implemented based on said projected user pupil location.

20. A digital display device operable to automatically adjust a digital image to be rendered thereon, the device comprising:
a digital display medium;
a hardware processor; and a pupil tracking engine operable by said hardware processor to automatically:
receive as input sequential user pupil locations;
digitally compute from said sequential user pupil locations an estimated physical trajectory of said user pupil location over time; and digitally predict from said estimated trajectory a predicted user pupil location for a projected time;
wherein said hardware processor is operable to adjust the digital image to be rendered via said digital display medium at said projected time based on said predicted user pupil location.

21. The digital display device of claim 20, wherein said pupil tracking engine is further operable to automatically acquire said sequential user pupil locations.

22. The digital display device of claim 21, further comprising at least one camera, and wherein said pupil tracking engine is operable to interface with said at least one camera to acquire said user pupil locations.

23. The digital display device of claim 22, further comprising at least one light source operable to illuminate said user pupil locations, wherein said pupil tracking engine is operable to interface with said at least one light source to acquire said user pupil locations.

24. The digital display device of claim 23, wherein said at least one light source comprises an infrared or near infrared light source.

25. The digital display device of any one of claims 21 to 24, wherein said pupil tracking engine is operable to computationally locate said user pupil locations based on at least one of a machine vision process or a glint-based process.

26. The digital display device of any one of claims 20 to 25, wherein the device is operable to adjust a user perception of the digital image to be rendered thereon, the device further comprising:
a light field shaping layer (LFSL) disposed relative to said digital display medium so to shape a light field emanating therefrom and thereby at least partially govern a projection thereof toward the user;
wherein said hardware processor is operable to output adjusted image pixel data to be rendered via said digital display medium and projected through said LFSL
so to produce a designated image perception adjustment when viewed from said predicted user pupil location.