JP7258291B2 - Image generation device and image generation method - Google Patents

Description

The present invention relates to an image generation device and an image generation method.

2. Description of the Related Art Conventionally, a modeling apparatus (3D printer) that models a modeled object using an inkjet head is known (see, for example, Patent Document 1). In such a modeling apparatus, for example, a modeled object is modeled by lamination modeling by stacking a plurality of layers of ink formed by an inkjet head.

JP 2015-071282 A

2. Description of the Related Art When a modeling apparatus forms a modeled object, it is possible to model a high-definition modeled object based on data designed on a computer by a user such as a designer. However, depending on the shape of the modeled object, the texture of the modeled object may deviate from the texture desired by the user. Further, for example, depending on the intended use of the modeled object, it may be desired to match the texture of the modeled object with the texture predicted by the user in advance with higher accuracy. Therefore, conventionally, it has been desired to predict the texture of a modeled object with higher accuracy before actually forming the modeled object. SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide an image generating apparatus and an image generating method that can solve the above problems.

The inventors of the present application conducted intensive research on a method for predicting the texture of a modeled object with higher accuracy when the modeled object is modeled by the layered manufacturing method. First, the inventors focused on the fact that the texture of the modeled object differs depending on the position on the surface. More specifically, when modeling is performed using the additive manufacturing method, the side surface of the modeled object tends to become a rough surface with a rough feeling due to the exposure of the boundary between the layers of the modeling material (for example, the ink layer). . On the other hand, since the top surface of the modeled object is a surface on which flattened ink dots are arranged, for example, it tends to be a smoother surface than the side surface. Further, in the case of performing modeling by the layered manufacturing method, it is widely performed to flatten the layer of the material for modeling by a flattening means such as a roller. In this case, it is conceivable that the flattened upper surface becomes a smoother surface, and the difference in texture between the upper surface and the side surfaces increases.

On the other hand, the inventor of the present application predicts the texture of the modeled object in advance by creating a computer graphics image that reflects the surface condition of the modeled object in more detail before modeling the modeled object. I thought. Also, in this case, by measuring a plurality of samples each having surfaces with different angles of inclination with respect to the plane, and using the acquired parameters, the inclination of the surface that constitutes each position on the surface of the object can be determined. I thought about changing the texture on the computer graphics image according to the angle. In addition, as such parameters, the inventors considered using a parameter indicating how light is reflected by a surface and a parameter indicating the state of unevenness formed on the surface of the surface. By actually conducting various experiments, it was confirmed that the texture of a modeled object can be appropriately predicted by such a method.

Further, the inventors of the present application have conducted further intensive research and found the characteristics necessary to obtain such effects, and have completed the present invention. In order to solve the above-described problems, the present invention provides the three-dimensional data representing a planned object to be formed by a modeling apparatus that forms an object by laminating layers of modeling materials. An image generating apparatus for generating a computer graphics image representing a planned object, comprising: a parameter storage unit for storing parameters used for representing a state of a surface constituting the planned object in a computer graphics image; an image generation unit that generates a computer graphics image showing the planned object, wherein the parameters are obtained by measuring a plurality of samples each having surfaces with different angles of inclination with respect to the horizontal plane. and each of the plurality of samples is a modeled object created in advance by a modeling apparatus, and the parameter storage unit stores, as the parameters, a reflection state parameter that indicates how light is reflected by a surface, a surface and an uneven state parameter, which is a parameter indicating the state of unevenness formed on the surface of the surface, is stored in association with the inclination angle of the surface, and the image generation unit stores the three-dimensional data, the reflection state parameter, and the uneven state A computer graphics image representing the planned object is generated based on the parameters.

With this configuration, for example, it is possible to appropriately predict the texture associated with how light is reflected and unevenness for each position constituting the surface of the modeled object. Also, this makes it possible to appropriately check the texture of a modeled object using a computer graphics image, for example, before actually forming the modeled object.

Further, in this configuration, the image generating unit, for example, controls the reflection of light at each position based on the reflection state parameter and the unevenness state parameter corresponding to the inclination angle of the surface at each position constituting the surface of the planned object. A computer graphics image is generated to represent the way and the condition of the unevenness. With this configuration, for example, it is possible to more appropriately check the texture of the modeled object.

Also, the parameter storage unit stores, as reflection state parameters, BRDF information, which is information obtained by performing BRDF measurements on a plurality of samples, for example. In addition, normal line information, which is information obtained by measuring the normal line direction at each position on the surface of a plurality of samples, is stored as the unevenness state parameter, for example. With this configuration, for example, it is possible to more appropriately predict textures related to how light is reflected and unevenness. Further, in this case, the image generation unit performs bump mapping on each position constituting the surface of the planned object based on the normal line information corresponding to the inclination angle of the surface at each position. Also, the BRDF is set based on the BRDF information corresponding to the inclination angle of the surface at each position. With this configuration, for example, the texture of the modeled object can be expressed (reproduced) more appropriately in the computer graphics image.

Further, in this configuration, the image generation device includes, for example, a reception unit that receives an instruction from a user specifying the orientation of the planned object to be displayed in the computer graphics image, and displays the computer graphics image generated by the image generation unit. You may further have a display part. Further, in this case, when the receiving unit receives an instruction to change the orientation of the planned object, the image generating unit generates, for example, a computer graphics image showing the planned object in the changed orientation. Also, the display unit displays, for example, a computer graphics image showing the planned object in the changed orientation. With this configuration, for example, it is possible to confirm changes in texture and the like while changing the orientation of the planned object in the computer graphics image. In addition, this makes it possible to appropriately select, for example, the preferred orientation of the planned object. Further, in this case, the reception unit may further receive an instruction from the user to specify, for example, the orientation of the planned object in the computer graphics image displayed on the display unit as the orientation at the time of modeling. With this configuration, for example, it is possible to more appropriately designate the orientation of the modeled object at the time of modelling.

Further, in this configuration, it is conceivable to predict the occurrence of lamination fringes by using the reflection state parameter and the unevenness state parameter. In this case, the lamination stripes are, for example, a striped pattern generated by laminating layers of modeling material. More specifically, in this case, the image generation device further includes, for example, a stacking fringe prediction unit that predicts the generation of stacking fringes. In addition, the lamination fringe prediction unit predicts, for example, based on the three-dimensional data, the reflection state parameter, and the irregularity state parameter, a region where lamination fringes that meet the criteria set in advance at the time of modeling of the object corresponding to the planned object will occur. and notify the user. In this case, the stacking fringes satisfying the preset criteria are, for example, the stacking streaks that pose a problem in the desired modeling quality. With this configuration, for example, lamination fringes can be predicted appropriately. Further, in this case, for example, by appropriately changing the orientation of the planned object in the computer graphics image, it is possible to search for an orientation in which the lamination fringes are less conspicuous.

Further, in this case, for example, the receiving unit may receive designation of a partial region of the planned object from the user as the region in which the generation of lamination fringes is predicted. In this case, the stacking fringe prediction unit predicts the state of stacking fringes that will occur in a partial region specified by the user, for example. With this configuration, for example, it is possible to predict the occurrence of lamination streaks by designating a particularly important position in the modeled object.

Further, in this case, the lamination fringe prediction unit further predicts the state of lamination fringes that will occur on the surface that constitutes the above partial area when the orientation of the planned object to be displayed in the computer graphics image is changed, In addition, the user may be presented with an orientation of the planned object that makes the lamination stripes less conspicuous. With this configuration, for example, it is possible to more easily and appropriately select the preferred orientation of the modeled object.

Moreover, in this configuration, the image generation device may further include a modeling data generation unit and the like. In this case, the modeling data generation unit is, for example, a configuration that generates modeling data representing a modeled object in a state in which the orientation at the time of modeling is specified. Also, in this case, for example, it is conceivable to generate modeling data based on the orientation at the time of modeling specified by the user. Further, when the generation of lamination fringes is predicted as described above, modeling data may be generated using the prediction result. In this case, for example, it is conceivable to determine the orientation of the modeled object at the time of modeling based on how the predicted formation of lamination stripes occurs, and to generate modeling data.

Also, as a configuration of the present invention, it is conceivable to use an image generation method having the same characteristics as described above. Further, as the configuration of the present invention, for example, a modeling apparatus and modeling method for modeling a modeled object using this image generating method, and a program for operating a computer as the image generating apparatus as described above may be considered. can. Also in these cases, for example, the same effect as described above can be obtained.

According to the present invention, for example, computer graphics images can be used to appropriately confirm the texture of a modeled object.

It is a figure explaining modeling system 10 concerning one embodiment of the present invention. FIG. 1(a) shows an example of the configuration of the modeling system 10. As shown in FIG. FIG. 1(b) shows an example of the configuration of the main part of the modeling device 12 in the modeling system 10 together with the modeled object 50. As shown in FIG. FIG. 1(c) is a diagram for explaining the texture that changes according to the inclination angle of the surface. FIG. 10 is a diagram showing an overview of how texture is reflected in a CG image generated in this example; It is a figure which shows an example of several samples used in this example. FIG. 3(a) shows an example of the configuration of the sample. FIG. 3(b) is a diagram for explaining the tilt angle of the surface of the sample. It is a figure which demonstrates in more detail about the measurement of a normal-line map. FIG. 4A shows an example of an image capturing environment used when measuring a normal map. FIG. 4B shows an example of imaging results for one sample. FIG. 4 is a diagram showing an example of normal maps corresponding to each of a plurality of samples; FIG. 10 is a diagram for explaining in more detail how to express the state of unevenness in a CG image; It is a figure which shows an example of the measurement environment of BRDF. 4 is a diagram for explaining in more detail the CG image generated by the control PC 14. FIG. FIG. 8(a) shows the sample used to acquire the normal map and BRDF. FIG. 8B shows an example of a CG image generated using a normal map obtained by measurement and BRDF. FIG. 10 is a diagram showing an example of a CG image showing a modeled object having a shape different from that of a sample; FIG. 5 is a diagram for explaining in more detail the relationship between the orientation of a modeled object and the texture of the surface; FIG. 10(a) shows an example of a CG image showing a modeled object in a direction that causes a difference in texture between the upper surface and the side surface. FIG. 10(b) shows an example of a CG image showing a modeled object in an orientation in which the difference in texture between the top surface and the side surface is small. It is a figure which shows an example of a structure of control PC14. 4 is a flowchart showing an example of an operation of generating modeling data representing a modeled object to be modeled by the modeling apparatus 12. FIG.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments according to the present invention will be described with reference to the drawings. FIG. 1 is a diagram illustrating a modeling system 10 according to one embodiment of the present invention. FIG. 1(a) shows an example of the configuration of the modeling system 10. As shown in FIG. FIG. 1(b) shows an example of the configuration of the main part of the modeling device 12 in the modeling system 10 together with the modeled object 50. As shown in FIG. In this example, the modeling system 10 is a system for modeling a three-dimensional object, and includes a modeling device 12 and a control PC 14 . Also, except as noted below, the modeling system 10 may have features that are the same as or similar to known modeling systems.

The modeling apparatus 12 is an apparatus that executes modeling of the modeled object 50, and models the modeled object 50 by layered modeling by laminating ink layers. In this case, ink is, for example, a functional liquid. Also, in this example, ink is an example of a material for modeling. Ink can also be considered as, for example, a liquid ejected from an inkjet head. In this case, the inkjet head is, for example, an ejection head that ejects liquid by an inkjet method.

More specifically, in this example, the modeling apparatus 12 has a head section 102 configured to eject ink toward a modeled object 50 being modeled, as shown in FIG. 1B, for example. The head section 102 also has a carriage 200 , a plurality of inkjet heads 202 , an ultraviolet light source 204 and rollers 206 . The carriage 200 is a holding member that holds other components of the head section 102 . In addition, the plurality of inkjet heads 202 are ejection heads that eject ink, which is a material for modeling. In this example, the plurality of inkjet heads 202 eject ultraviolet curable ink, which is ink that is cured by being irradiated with ultraviolet rays. Also, each of the plurality of inkjet heads 202 ejects inks of different colors, for example. With this configuration, for example, the ink layer 152 can be appropriately formed by ejecting ink from the plurality of inkjet heads 202 . In addition, by using a plurality of different colors of ink, for example, the colored modeled object 50 can be appropriately modeled.

The ultraviolet light source 204 is curing means for curing the ink ejected by the plurality of inkjet heads 202 . The roller 206 is a flattening means for flattening the ink layer 152, and for example, flattens the ink layer 152 by scraping off part of the ink before being irradiated with ultraviolet rays.

In addition to the head section 102 shown in FIG. 1B, the modeling apparatus 12 further includes the same or similar configuration as that of a known modeling apparatus. More specifically, the modeling apparatus 12 controls, for example, a scanning drive unit that causes the head unit 102 to perform a scanning operation to move relative to the object 50 being modeled, and the operation of each part of the modeling apparatus 12. It may further have a control unit and the like. In this case, the scanning drive unit performs, for example, a main scanning operation in which ink is ejected while moving relative to the modeled object 50 in a predetermined main scanning direction, and a main scanning operation in which ink is ejected while moving relative to the modeled object 50 in the stacking direction. The head unit 102 is caused to perform a scanning operation such as scanning in the stacking direction and a sub-scanning operation of moving relative to the modeled object 50 in the sub-scanning direction. In this case, the stacking direction is the direction in which the ink layers 152 are stacked. Also, the sub-scanning direction is a direction orthogonal to the main scanning direction and the stacking direction. Making the head unit 102 perform a scanning operation means, for example, making the plurality of inkjet heads 202 in the head unit 102 perform a scanning operation.

Further, in each main scanning operation, the control unit causes the plurality of inkjet heads 202 to eject ink to ejection positions determined based on modeling data received from the control PC 14 . With this configuration, for example, each ink layer 152 that constitutes the modeled object 50 can be appropriately formed. Moreover, thereby, the modeled object 50 can be appropriately modeled by a lamination-modeling method, for example.

The control PC 14 is a computer that operates according to a predetermined program, and controls the operation of the modeling apparatus 12 by supplying modeling data indicating the modeled object 50 to be modeled to the modeling apparatus 12 . In addition, in the following, when distinguishing between the modeled object 50 that is being modeled by the modeling apparatus 12 and the modeled object 50 that has been modeled, the modeled object 50 that is to be modeled will be referred to as the planned model as necessary. It's called a thing. Further, in this example, the control PC 14 generates modeling data to be supplied to the modeling apparatus 12 based on the three-dimensional data representing the planned object to be modeled. In this case, as the three-dimensional data, for example, data in which the orientation (layout) of the modeled object 50 at the time of modeling is not specified is used. As the modeling data, for example, data specifying the orientation of the modeled object 50 at the time of modeling is used.

Further, in this example, the control PC 14 designates the orientation in the modeling data by receiving an instruction to designate the orientation of the modeled object 50 at the time of modeling from a user such as a designer who created the stereoscopic data. In this case, the user's instruction is received while showing the user a computer graphics image (hereinafter referred to as a CG image) showing the intended object. Thus, in this example, the control PC 14 also functions as an image generation device that generates a CG image representing the planned object based on the three-dimensional data representing the planned object. Further, in this case, as the CG image created by the control PC 14, a CG image reflecting the state of the surface of the modeled object 50 is created. More specifically, the texture that changes according to the inclination angle (modeling angle) of the surface is reflected as the state of the surface of the modeled object 50 .

FIG. 1(c) is a diagram for explaining the texture that changes according to the inclination angle of the surface, and shows an example of the difference in texture that occurs between the upper surface and the side surfaces of the modeled object 50. FIG. In this case, the upper surface is the uppermost surface in the stacking direction. The upper surface can also be considered as a surface corresponding to the surface of the ink layer 152 that is laminated last. A side surface is a surface that intersects with the top surface.

As can be understood from the illustrated configuration and the like, when modeling is performed by the layered manufacturing method, the side surface of the modeled object 50 includes many boundaries of the ink layers 152 . In this case, the boundary of the layer 152 is exposed, and the surface tends to be rough with a rough feeling. On the other hand, the upper surface of the modeled object 50 is a surface on which flattened ink dots are arranged, and thus tends to be smoother than the side surface. Moreover, when the layer 152 is flattened by the roller 206 in the head section 102 as in this example, the upper surface becomes a smoother surface due to the flattening effect.

Therefore, when the modeled object 50 is modeled by the layered manufacturing method, it is generally considered that the difference in texture between the upper surface and the side surface of the modeled object 50 becomes large. On the other hand, in this example, as described above, as the CG image created by the control PC 14, an image reflecting the texture that changes according to the inclination angle of the surface is generated. With this configuration, for example, the texture of the modeled object 50 can be appropriately predicted with higher accuracy before the modeled object 50 is actually modeled by the modeling apparatus 12 . In addition, as a result, for example, it is possible to appropriately adjust the orientation of the modeled object 50 at the time of modeling, if necessary. Therefore, the CG image created by the control PC 14 will be described in more detail below.

FIG. 2 is a diagram showing an overview of how texture is reflected in a CG image generated in this example. As shown in the figure, in this example, the texture of the planned object is expressed by creating a CG image reflecting parameters acquired from a sample created in advance. In this case, the sample can be considered to be, for example, a modeled sample, which is a modeled object created in advance by the modeler 12 (see FIG. 1). Further, in this case, as the modeling device 12, it is conceivable to use the same device as the modeling device 12 that models the modeled object 50. FIG. A device that is the same as the modeling device 12 that models the modeled object 50 is, for example, a device that models the modeled object 50 under the same conditions as when the modeled object 50 was modeled. In this case, the device that performs modeling under the same conditions is not limited to, for example, the same device as the modeling device 12 used to model the modeled object 50, and may be, for example, another modeling device 12 of the same model. In addition, different models of devices may be used as long as modeling can be performed under substantially the same conditions for the desired modeling quality and the like. Moreover, it is more preferable that the sample is created by the modeling apparatus 12 (the same modeling apparatus 12) that forms the modeled object 50 .

Further, in this example, a plurality of samples each having a surface with a different angle of inclination with respect to the horizontal plane are created, and predetermined measurements are performed on these samples to obtain parameters used when creating a CG image. get. In this case, the plurality of samples each having surfaces with different angles of inclination with respect to the horizontal plane is, for example, a plurality of samples with surfaces to be measured with different angles of inclination. In this example, as shown in the figure, parameters obtained by measuring a normal map and BRDF (Bi-directional Reflectance Distribution Function) are used as such parameters.

In this case, the normal map is measured using, for example, a known photometric stereo method. A parameter obtained by measuring the normal map is an example of an uneven state parameter, which is a parameter indicating the state of unevenness formed on the surface of the surface. The parameters obtained by measuring the normal map can also be considered as normal information, which is information obtained by measuring the normal direction of each position on the surface of a plurality of samples, for example. . Also, the BRDF is measured using, for example, a known goniophotometer. A parameter obtained by measuring BRDF is an example of a reflection state parameter, which is a parameter indicating how light is reflected by a surface. The parameters obtained by measuring the BRDF can also be considered, for example, BRDF information, which is information obtained by measuring the BRDF for a plurality of samples.

In this example, a CG image that expresses the texture of the planned object is generated by performing processing (for example, rendering) for generating a CG image so as to reflect the above parameters. More specifically, in this case, the control PC 14, for example, based on each parameter corresponding to the inclination angle of the surface at each position constituting the surface of the planned object, determines the state of unevenness and light intensity at each position. A CG image is generated so as to express the way of reflection. More specifically, in this example, bump mapping is performed based on the normal map to express the uneven state. In this case, for the operation of performing bump mapping based on the normal map, for example, for each position constituting the surface of the planned object, bump mapping is performed based on normal information corresponding to the inclination angle of the surface at each position. It can also be considered as an operation of performing mapping or the like. Also, by setting a BRDF according to the tilt angle for each position of the CG image, the way light is reflected is expressed. In this case, the operation of setting the BRDF can be considered, for example, the operation of setting the BRDF based on the BRDF information corresponding to the inclination angle of the surface at each position.

With this configuration, the texture on the CG image can be varied according to, for example, the inclination angles of the surfaces forming each position on the surface of the planned object. In addition, this makes it possible to more appropriately express (reproduce) the texture of a modeled object in a CG image, for example. Therefore, according to the present example, it is possible to more appropriately predict and confirm the texture of the modeled object related to the way light is reflected and the unevenness of the modeled object, for example, before the modeled object is actually modeled.

Next, the CG image generated in this example will be described in more detail. First, the configuration and the like of the sample used in this example will be described. FIG. 3 shows an example of a plurality of samples used in this example. FIG. 3A is a diagram showing an example of the configuration of a sample, and shows the configuration of one of the samples used in experiments by the inventors of the present application. FIG. 3(b) is a diagram for explaining the tilt angle of the surface of the sample.

In this example, as the sample, a plate-like sample can be preferably used as shown in FIG. 3(a), for example. Also, in this case, for a plurality of specimens each having surfaces with different angles of inclination with respect to the horizontal plane, for example, as shown in FIG. be able to. In this case, creating a sample with different orientations during modeling means, for example, using a support layer as appropriate to vary the orientation of the sample during fabrication. The support layer is, for example, a structure used to support a part of a modeled object that is being modeled, such as a modeled object having an overhang shape. A support layer is typically formed as needed during the build and removed after the build is complete. In this case, the support layer may be formed of, for example, a water-soluble material. With this configuration, for example, the support layer can be appropriately removed with water after the modeling of the modeled object is completed.

More specifically, in this example, as shown in the figure, the inclination angle of the main surface of the sample with respect to the horizontal plane is changed in increments of 15° within the range of 0° to 90°. , 7 samples were prepared. The main surface of the sample is, for example, the widest surface of the sample. In addition, the main surface of the sample can be considered as, for example, a surface of the sample that is the target for normal map or BRDF measurement.

A 3DUJ-533 device, which is a modeling device (3D printer) manufactured by Mimaki Engineering Co., Ltd., was used to prepare the samples. In this case, as the modeling device 12 used in the modeling system 10 of this example, it is conceivable to use a 3DUJ-533 device, which is a modeling device (3D printer) manufactured by Mimaki Engineering Co., Ltd. Further, in this case, it is conceivable to form a modeled object colored in full color by using inks of cyan, magenta, yellow, and black, for example. In this case, it is preferable to prepare a plurality of samples for various colors. However, for convenience of explanation, the characteristics of this example will be mainly explained for the case where a plurality of samples of one color are used. More specifically, in the experiment conducted by the inventors of the present application, the color of the sample was set to be the same color as the central color of the logo of Chiba University. In this case, for the sample colors, for example, the density of cyan ink is 0%, the density of magenta ink is 100%, the density of yellow ink is 70%, and the density of black ink is 20%. It can be considered as a color etc. Also, when modeling an object that is colored in full color, the texture related to unevenness on the surface of the modeled object is obtained using parameters obtained by measuring multiple samples of one color. , can be predicted. Therefore, even when forming a modeled object that is colored in full color, only a plurality of samples of one color may be used as the plurality of samples.

Next, a more detailed description will be given of the measurement performed on a plurality of samples, the use of the measurement results, and the like. FIG. 4 is a diagram for explaining in more detail the measurement (acquisition) of the normal map. FIG. 4A shows an example of an image capturing environment used when measuring a normal map. FIG. 4(b) is a diagram showing an example of photographing results for one sample (sample corresponding to one tilt angle). show.

As explained above, the measurement of the normal map can be performed using a known photometric stereo method. In this case, the photometric stereo method can be considered, for example, as a method of obtaining a normal vector at a position corresponding to a pixel on the surface of an object from a ratio of pixel values of the object in three or more images with different light source directions. can. More specifically, in this example, a dome-shaped photographing environment in which light sources were installed at a plurality of positions was prepared, and an image of each sample was photographed. Moreover, LED was used as a light source. Further, the LEDs were arranged evenly along the dome at the positions indicated by numbers 1 to 9 in FIG. 4(a), for example. With this configuration, the light source direction (illumination position) can be changed in various ways by, for example, switching the LEDs to be lit. In addition, by using the above-described dome-shaped imaging environment, it is possible to appropriately prevent other conditions from acting when the lighting position is changed.

In addition, regarding points other than the above, it can be performed in the same or similar manner as the known photometric stereo method. In this case, the known photometric stereo method is, for example, a method of obtaining a normal map using a plurality of images with different lighting positions and a mask image corresponding to the object to be photographed. be. A normal map is, for example, an image representing the direction of a normal vector at an arbitrary position of an object. In this example, as the normal map, an image is used in which the xyz components representing the direction of the normal vector at an arbitrary position of the object are changed in correspondence with the RGB values. In addition, the photometric stereo method can also be considered as a method of obtaining the normal vector of the corresponding pixel on the surface of the object from the ratio of the pixel values of the object in three or more images with different light source directions. In this case, for example, a perfect diffusion model is assumed for the object for which the normal map is to be obtained. Focusing on the fact that the observed luminance changes depending on the angle formed by the incident light and the normal, the normal vector is determined.

More specifically, in this case, if the unit normal vector is n, the unit incident light vector is s, the diffuse reflectance is ρ, and an arbitrary observed luminance is i under three types of known light sources, i is equal to the inner product of s and n multiplied by ρ (i=ρs·n). Therefore, the smaller the angle between the incident light and the normal, the larger the observed brightness for that pixel. Further, in this case, the value of the vector ρn is expressed by the following equation ρn=(s ^T s) ^T (s ^T i) by using the Moore-Penrose pseudo-inverse matrix.
can be obtained using Also, the normal vector n can be obtained by normalizing the vector ρn.

Further, in this case, by capturing a plurality of images for each of the plurality of samples, normal maps corresponding to the respective samples can be obtained as shown in FIG. FIG. 5 is a diagram showing an example of a normal map corresponding to each of a plurality of samples. For the image representing the normal map, after adjusting the contrast to make it easier to recognize the difference between the samples, Shown as a grayscale image.

As can be seen from the figure, in the sample corresponding to the 0° inclination angle (formation angle), the change in the normal direction is small due to the flattening by the roller 206 (see FIG. 1). On the other hand, when the inclination angle increases, the influence of the portion not flattened by the roller 206 increases, and the normal direction changes finely. Also, from these results, it can be considered that the normal map reflects, for example, the state of fine unevenness on the surface.

Also, as described above, in this example, the CG image expresses the state of unevenness. As a method for that purpose, for example, as shown in FIG. 6, bump mapping is performed based on the normal map. FIG. 6 is a diagram for explaining in more detail the representation of the state of unevenness (reproduction of unevenness) performed in a CG image.

In this case, bump mapping can be considered, for example, as a method of expressing unevenness on the surface of a three-dimensional object. Further, in bump mapping, for example, fluctuations in the normal vector used to calculate shadows on the surface of an object represented by a CG image correspond to fluctuations in the luminance value of the texture image, thereby giving fluctuations to the surface of the object so that the appearance can be matched to the uneven state. to achieve

More specifically, in this example, each pixel (pixel ), apply this texture image. Further, in this way, for example, the reflection direction of the light striking the surface of the object shown by the CG image is changed in a pseudo manner. With this configuration, it is possible to make the surface of the CG image appear to have minute unevenness depending on the degree of gradation, for example. Also, in this case, for example, by simply inputting a texture image with luminance changes without actually changing the shape of the object, the state of three-dimensional unevenness can be appropriately adjusted, for example, as shown in the enlarged view in the figure. can be reproduced. Therefore, with such a configuration, for example, high-speed rendering and the like can be performed more appropriately without greatly increasing the amount of computational processing.

Also, in this example, bump mapping is performed for each position on the surface of the planned object in the CG image according to the tilt angle at that position. In this case, if the tilt angle at each position is different from the tilt angles of any sample, for example, it is possible to use the normal map corresponding to the sample with the closest tilt angle. In addition, when trying to express unevenness with higher accuracy, interpolation processing is performed using normal maps of multiple samples to calculate a normal map corresponding to an arbitrary tilt angle. You may According to this example, for example, in a CG image showing a planned object, it is possible to appropriately express the state of unevenness according to the inclination angle of the surface.

As for the texture image used in bump mapping, it is conceivable to appropriately change the size or the like in accordance with the area to which the texture image is applied in the CG image. Also, in this case, for example, a known method such as image quilting can be preferably used. In addition, it is conceivable that the operation such as bump mapping is performed in the same or similar manner as the known operation such as bump mapping except for the above points. Also, as a method for expressing unevenness and the like in a CG image, a method other than bump mapping may be used. In this case, for example, it is conceivable to use a known method for expressing granular unevenness.

Also, as described above, in this example, BRDF measurements are further performed for a plurality of samples. FIG. 7 is a diagram showing an example of a BRDF measurement environment, showing an environment in which BRDF was measured in an experiment conducted by the inventors of the present application. As shown in the figure, in this example, a sample used as a measurement target is irradiated with light from a light source. Then, the light reflected from the sample is measured at the light receiving portion.

Here, the BRDF can be considered, for example, as a function or the like indicating the reflectance corresponding to the combination of the incident direction and the reflected direction of light. Therefore, for BRDF, the reflectance is measured while variously changing the angle corresponding to each of the incident direction and the reflection direction. Also, in this case, a known goniophotometer or the like can be suitably used as the measuring device.

In addition, in order to obtain high-density measurement results for BRDF, it is necessary to reduce the step width for changing the direction of incidence and the direction of reflection, and perform measurements an enormous number of times. However, if an enormous number of measurements are performed in this way, the trouble and time required for the measurements will increase greatly. Therefore, for BRDF measurement, it is preferable to use known methods for efficient measurement to minimize the required number of measurements. In this case, for example, by assuming that the BRDF is isotropic, the BRDF for each azimuth angle with respect to an arbitrary tilt angle and the BRDF for each tilt angle with respect to an arbitrary azimuth angle may be equal.

In addition, depending on the specifications of the device (goniophotometer, etc.) used for BRDF measurement and the measurement environment, BRDF measurement corresponding to some angles may not be possible. In such a case, it is conceivable to estimate the BRDF of an angle that cannot be measured based on the BRDF of another angle that is normally measured. More specifically, in this case, for example, it is conceivable to estimate an unknown BRDF by fitting reflectance values corresponding to correctly measured angles to an existing BRDF model. As an existing BRDF model, for example, a model using the sum of a diffuse reflection component term and a specular reflection component term (for example, a Torrance Sparrow model, etc.) can be preferably used.

Also, as explained above, in this example, the tilt angle of the sample is set in increments of 15°. Therefore, BRDF measurement can also be performed only for surfaces with some tilt angles. However, in order to express the quality of the modeled object in a CG image with higher accuracy, it is desirable to acquire the BRDF for a plane with an arbitrary tilt angle. Therefore, in this example, the BRDF is calculated by performing an interpolation process based on the BRDF obtained by measurement for a plane with an inclination angle for which no corresponding sample exists. In this case, as for the interpolation processing, for example, it is conceivable to perform calculation by performing spline interpolation using BRDFs obtained by measuring a plurality of samples. With this configuration, for example, it is possible to appropriately acquire a BRDF corresponding to a surface with an arbitrary tilt angle.

Also, as described above, in this example, the control PC 14 (see FIG. 1) generates a CG image reflecting the texture corresponding to the tilt angle of the surface. Also, in this case, the texture is expressed based on the normal map and BRDF obtained using the sample.

FIG. 8 is a diagram for explaining in more detail the CG image generated by the control PC 14. As an example of the CG image, FIG. 8 shows the result of CG reproduction of a sample with an inclination angle of 15°. FIG. 8(a) is a diagram showing a sample used to acquire the normal map and the BRDF, and shows a photograph of the actual sample used as the sample with an inclination angle of 15°. FIG. 8(b) is a diagram showing an example of a CG image generated using a normal map obtained by measurement and BRDF. An example of a CG image generated by performing rendering etc. reflecting the line map and BRDF is shown. Although it is somewhat difficult to understand in the drawings shown in grayscale images, it was confirmed that the color images and unevenness of the actual sample can be appropriately reproduced in the CG images in the color images corresponding to FIGS. Further, when forming an actual modeled object, the modeled object is not limited to the same shape as the sample, and various shapes of the modeled object are modeled. Therefore, it is also necessary to generate CG images showing various shapes of objects (planned objects) in various directions.

FIG. 9 is a diagram showing an example of a CG image showing a modeled object having a shape different from that of a sample, and shows CG images of a cubic modeled object with various orientations. In the figure, the figure on the upper left side is an example in which the angle of inclination of the upper surface is set to 0° so that the upper surface, which is the upper surface of the cube, is parallel to the horizontal plane. In this case, the angle of inclination of the sides of the cube is 90°. Also, each drawing other than the upper left side is an example in which the inclination angles of the upper surface and the side surface are variously changed.

Each CG image was generated by using stereoscopic data representing a cube and performing rendering or the like in a state in which a normal map and BRDF corresponding to the inclination angle of the surface are reflected for each of the top surface and the side surface. Also, in this case, as described above, for the BRDF, interpolation processing was performed according to the inclination angle of the surface as necessary for each surface. For the normal map, interpolation processing was not performed for simplification of processing, and the measurement result for the sample with the inclination angle closest to the inclination angle of each surface was used. Also, as described above, the reflection of the normal map was performed by bump mapping.

As shown in the drawing, changing the orientation of the cube changes the texture of each surface in the CG image. Therefore, according to this example, for example, it is possible to appropriately check the texture of the model that is actually modeled in association with the orientation of the modeled object at the time of modelling. In this case, for example, by changing the orientation of the modeled object shown in the CG image according to the user's instruction, the user can confirm the change in texture due to the change in orientation, and the orientation of the modeled object at the time of modeling can be confirmed. It is conceivable to decide

FIG. 10 is a diagram for explaining in more detail the relationship between the orientation of the modeled object and the texture of the surface. FIG. 10(a) shows an example of a CG image showing a modeled object in a direction that causes a difference in texture between the upper surface and the side surface. FIG. 10(b) shows an example of a CG image showing a modeled object in an orientation in which the difference in texture between the top surface and the side surface is small. As described above, the texture of each surface in the CG image reflects the irregularities and the like that occur on the surface during modeling. Therefore, the CG image shown in FIG. 10(a) can be considered as an example of a case in which the difference in surface irregularities is large depending on the surface. Also, the CG image shown in FIG. 10B can be considered as an example in which the difference in surface unevenness between surfaces is small.

Here, it is conceivable that the texture required for a modeled object changes in various ways depending on the purpose of the modeled object and the like. In contrast, in this example, for example, by showing the user CG images showing the modeled object in various orientations, the user can appropriately select the orientation of the modeled object that gives the desired texture. Therefore, according to this example, it is possible to appropriately check the texture of the modeled object using, for example, a CG image. Also, in this case, by matching the direction of the modeled object when the modeled object is modeled by the modeling apparatus 12 (see FIG. 1) to the direction selected by the user, the modeled object can be appropriately modeled with the texture desired by the user. can be done.

Subsequently, supplementary explanations and the like regarding each configuration explained above will be given. First, the configuration of the control PC 14 used in this example will be described in more detail.

FIG. 11 is a diagram showing an example of the configuration of the control PC 14. As shown in FIG. In this example, the control PC 14 has a display section 302 , a reception section 304 , a storage section 306 and a control section 308 . Also, as described above, as the control PC 14, for example, a computer that operates according to a predetermined program can be used. In this case, each part of the computer can be considered to operate as each component of the control PC 14 .

A display unit 302 is a display device that displays a CG image generated by the control PC 14 . As the display unit 302, for example, a computer monitor or the like can be preferably used. Also, the reception unit 304 is an input device that receives a user's instruction. As the reception unit 304, for example, a computer input device (eg, mouse, keyboard, etc.) can be preferably used.

A storage unit 306 is a storage unit that stores data and the like used for generating a CG image. As the storage unit 306, a computer storage device (for example, HDD, etc.) can be preferably used. Further, in this example, the storage unit 306 is an example of a parameter storage unit, and at least the state of the surfaces constituting the object to be formed (planned object) to be formed by the forming apparatus 12 (see FIG. 1) is displayed as a CG image. Stores the parameters used to express in .

More specifically, in this example, the storage unit 306 stores parameters based on normal maps and BRDFs obtained by performing measurements on a plurality of samples as such parameters for each sample. Stored in association with the tilt angle. In this case, storing the parameters based on the normal map and BRDF may mean, for example, storing the measured normal map and BRDF as they are. As the parameters based on the normal map and BRDF, instead of using the measurement result as it is, for example, parameters generated by converting to a format that is easy to use when generating a CG image may be used. .

Also, as described above, in this example, the parameter obtained by measuring the normal map is an example of the uneven state parameter. A parameter obtained by measuring the BRDF is an example of a reflection state parameter. Therefore, it can be considered that the storage unit 306 stores, for example, the reflection state parameter and the unevenness state parameter in association with the inclination angle of the surface. Also, in this example, the storage unit 306 further stores three-dimensional data indicating the planned object to be molded. In this case, the stereoscopic data is input to the control PC 14 via, for example, a storage medium or network, and stored in the storage unit 306 .

The control unit 308 is configured to control the operation of each unit in the control PC 14 . As the control unit 308, for example, a CPU of a computer can be preferably used. Further, in this example, the control unit 308 functions as an image generation unit that generates a CG image representing the planned object by operating according to a predetermined program. In this case, the control unit 308 controls the three-dimensional data representing the planned object and the above-mentioned parameters stored in the storage unit 306 (the normal map obtained by measuring a plurality of samples and the parameters), a CG image showing the planned object is generated. By displaying the generated CG image on the display unit 302, the CG image is presented to the user.

Also, as described above, in this example, the control PC 14 may present to the user a CG image in which the orientation of the planned object is changed in various ways according to the user's instructions. In this case, for example, the receiving unit 304 receives from the user an instruction specifying the direction of the planned object to be displayed in the CG image. Further, when the receiving unit 304 receives an instruction to change the orientation of the planned object, the control unit 308 generates a new CG image showing the planned object in the changed orientation, for example. Further, the display unit 302 displays a CG image showing the planned object in the changed orientation, for example, by displaying a CG image newly created by the control unit 308 . With this configuration, for example, it is possible to appropriately confirm changes in texture and the like while changing the orientation of the planned object in the CG image. In addition, this makes it possible to appropriately select, for example, the preferred orientation of the planned object.

In this case, instead of simply changing the orientation of the planned object, the user can confirm the orientation of the planned object at the time of modeling by allowing the user to check the CG images corresponding to the planned object in various orientations. It is conceivable to let them choose. In this case, for example, the reception unit 304 may further receive an instruction from the user to designate the orientation of the planned object in the CG image displayed on the display unit 302 as the orientation at the time of modeling. By configuring in this way, for example, it is possible to appropriately receive the designation of the orientation of the modeled object at the time of modelling.

In this case, it is conceivable that modeling data is generated in the control unit 308 based on the orientation at the time of modeling specified by the user. In this case, the controller 308 can be considered to function as a modeling data generator. Further, the modeling data is, for example, as described above, data representing a modeled object in a state in which the orientation of the modeled object at the time of modeling is specified. Modeling data can also be considered as layout data or the like that indicates the modeled object along with the orientation and arrangement of the modeled object at the time of modelling, for example. Also, in this case, by supplying modeling data from the control PC 14 to the modeling apparatus 12 (see FIG. 1), the modeling apparatus 12 can be caused to perform the modeling operation in an orientation that matches the user's instruction.

Subsequently, the flow of the series of operations described above will be described again using the flowchart shown in FIG. 12 . FIG. 12 is a flow chart showing an example of the operation of generating modeling data representing a modeled object to be modeled by the modeling apparatus 12 . Further, in this case, the series of operations described above is from the operation of creating a sample to the operation of outputting modeling data.

As explained above, in this example, before creating the CG image, it is necessary to prepare the parameters used for creating the CG image. Then, in the step of preparing parameters, first, a plurality of samples are created in order to acquire parameters used for creating CG images (S102). Then, normal maps and BRDF are measured for a plurality of samples (S104), and parameters based on the measurement results are stored in the storage unit 306 (see FIG. 11) of the control PC 14. FIG. This also completes the step of preparing the parameters. In this case, the operation in step S102 is an example of the operation in the sample preparation stage. The operation of step S104 is an example of the operation of the parameter acquisition stage and the parameter storage stage.

In addition, as a step after the preparation of the parameters is completed, as described above, a CG image showing the planned object is generated. In this case, the operation of generating the CG image is an example of the operation in the image generation stage. In addition, in the operation of generating a CG image, first, three-dimensional data representing a planned object is input to the control PC 14 (S106). Then, an instruction specifying the orientation of the planned object in the CG image is received from the user (S108) as necessary, and the orientation (display orientation) of the planned object is specified. Further, in step 108, for example, if there is no user's instruction, it is conceivable to designate a preset standard orientation. After designating the orientation, a CG image is generated based on the stereoscopic data by reflecting the parameters stored in the storage unit 306 . Also, the generated CG image is displayed on the display unit 302 (see FIG. 11) (S110).

When an instruction is received from the user indicating that the orientation of the planned object displayed in the CG image is to be used as the orientation of the object during modeling (S112: Yes), that orientation is used as the orientation during modeling. Modeling data representing the object is generated and output (S114). Further, in step S112, no instruction is received from the user to adopt the orientation of the planned object displayed in the CG image as the orientation of the object during modeling, and the orientation of the object during modeling is not determined. If so (S112: No), the process returns to step S108, and, for example, receives an instruction from the user to change the orientation of the planned object in the CG image. By repeating the subsequent processes, a CG image showing the planned image in the newly set orientation is generated and displayed. With this configuration, it is possible to appropriately display CG images showing textures according to the orientations, for example, as CG images showing the planned object in various orientations. In addition, by displaying such a CG image, it is possible for the user to appropriately determine the orientation of the modeled object during modeling.

Next, application examples using CG images as described above will be described. As described above, in this example, the texture of the surface of the modeled object is predicted based on the normal map and BRDF obtained by measuring the sample. Also, as this texture, for example, texture caused by unevenness caused by the influence of the boundary of the laminated ink layers, etc., is predicted. Therefore, for the texture to be predicted in this example, for example, a texture related to so-called lamination stripes can be considered. In this case, the layered stripes are, for example, a striped pattern generated by stacking layers of ink used as a material for modeling.

Regarding this point, in the application example using the CG image as described above, for example, rather than simply generating a CG image that reproduces the state of the surface of the modeled object, it is possible to perform measurement on the sample. Based on the normal map and the BRDF acquired in 1., it is also conceivable to recognize and detect lamination fringes. More specifically, in this case, the control PC 14 further includes, for example, a stacking fringe prediction unit that predicts the generation of stacking fringes. The fact that the control PC 14 has a lamination fringe prediction section may mean, for example, that the control section 308 (see FIG. 10) in the control PC 14 functions as a lamination fringe prediction section.

Further, in this case, the control unit 308 functioning as a lamination fringe prediction unit is set in advance at the time of molding the modeled object corresponding to the planned modeled object, based on the three-dimensional data and the parameters stored in the storage unit 306, for example. Predict the region where lamination fringes that meet the criteria described above occur. In this case, the modeled object corresponding to the planned modeled object is, for example, a modeled object that is formed in the same orientation as the planned modeled object shown in the CG image. Further, the lamination fringes that satisfy a preset standard are, for example, lamination fringes that satisfy a standard that is set in accordance with the required modeling quality or the like. Further, the lamination fringes satisfying the criteria are lamination fringes that are more conspicuous than the lamination fringes corresponding to the criteria. Therefore, the lamination fringes that satisfy the preset criteria can be considered as lamination fringes or the like that pose a problem in the desired modeling quality, for example. Further, in this case, the control PC 14 notifies the user of the prediction result of the lamination fringes by displaying it on the display unit 302, for example. With this configuration, for example, lamination fringes can be predicted appropriately. Further, in this case, for example, by appropriately changing the orientation of the planned object in the CG image, it is possible for the user to search for an orientation in which lamination stripes are less noticeable. Also, the orientation of the planned object may be automatically changed based on the recognition result of the lamination stripes, for example. In this case, the configuration of the control PC 14 can be considered as, for example, a configuration that automatically recognizes the lamination stripes and changes the orientation of the modeled object so that the lamination stripes are less noticeable.

In this case, instead of predicting the occurrence of lamination fringes for the entire modeled object, it is also possible to have the user specify a partial region of the modeled object and predict the lamination streaks that will occur in that region. be done. More specifically, in this case, for example, it is conceivable to allow the user to specify an area in the modeled object whose appearance is particularly important, so that the modeled object is modeled in an orientation in which lamination stripes are less likely to occur in such an area. be done. Further, as such an important area, for example, in the case of forming a modeled object showing a human figure, it is conceivable to designate an area corresponding to a human face.

In this case, for example, the reception unit 304 of the control PC 14 receives designation of a partial region of the planned object as a region in which the generation of lamination fringes is predicted from the user. Then, the control unit 308 predicts, for example, the state of lamination fringes that will occur in the partial region designated by the user. With this configuration, for example, it is possible to predict the occurrence of lamination streaks by designating a particularly important position in the modeled object.

Moreover, in this case, it is preferable to further propose a direction in which the stacking fringes are particularly unlikely to occur in the designated area, instead of simply predicting the generation of the stacking fringes. More specifically, in this case, for example, not only the lamination stripes that occur in the direction of the planned object displayed in the CG image at that time, but also the specified area (partial It is conceivable to further predict the state of lamination stripes that occur on the surface that constitutes the area of . Also, in this case, based on the result of such prediction, it is conceivable to present to the user the orientation of the planned object in which the lamination fringes are less conspicuous. By configuring in this way, for example, it is possible to more easily and appropriately select the preferred orientation of the modeled object at the time of modelling. Further, when the modeling data is generated in the control unit 308, the modeling data may be generated using the prediction result of the lamination fringes. In this case, for example, it is conceivable to determine the orientation of the modeled object at the time of modeling based on how the predicted formation of lamination stripes occurs, and to generate modeling data.

Here, it is conceivable to recognize the lamination fringes based on, for example, the brightness contrast in the CG image. More specifically, at each position of the CG image, the local luminance contrast can be considered to change according to, for example, the rising angle of the convex portion on the surface of the modeled object. In addition, on the surface of the modeled object, such a location with a large rising angle can be considered to be a location where there is a high possibility that a convex portion with large undulations that rises at an acute angle exists, for example.

More specifically, it can be considered that the local luminance contrast in the CG image reflects, for example, the angle and height of the convex portion. Also, in this case, for example, it can be considered that there is a high possibility that a convex portion with a steep angle and a high height is present in a location where the luminance contrast is high. Also, in this case, in areas where the local contrast is high, there are protrusions with steep angles and high heights, which tend to form conspicuous lamination stripes in the actual modeled object. can be considered likely to become

Therefore, in order to recognize the lamination fringes, for example, a function (viewing function) indicating how to be viewed in association with the brightness of each position in the CG image is created, and the brightness is high and the contrast interval is high. It is conceivable, for example, to recognize a location with a small value as a location corresponding to lamination fringes. In this case, the location where the contrast interval is small is, for example, a location where a predetermined local difference in contrast occurs. Moreover, such a location can be considered to be, for example, a location with a high frequency of unevenness. Also, in this case, for example, by changing the orientation of the planned article, it is possible to select an orientation in which lamination stripes are less likely to occur in conspicuous or important areas of the article. With this configuration, for example, it is possible to more appropriately form a high-quality modeled object.

INDUSTRIAL APPLICABILITY The present invention can be suitably used, for example, in an image generation device.

DESCRIPTION OF SYMBOLS 10... Modeling system, 12... Modeling apparatus, 14... Control PC, 50... Modeled object, 102... Head part, 152... Layer, 200... Carriage, 202... Inkjet head 204 Ultraviolet light source 206 Roller 302 Display unit 304 Receiving unit 306 Storage unit 308 Control unit

Claims (13)

An image for generating a computer graphics image representing a planned object, which is an object to be modeled by a modeling apparatus that models a modeled object by laminating layers of modeling materials, based on three-dimensional data representing the planned object to be modeled. a generator,
a parameter storage unit for storing parameters used for expressing the state of the surface constituting the planned object with a computer graphics image;
an image generation unit that generates a computer graphics image showing the planned object,
The parameters are obtained by measuring a plurality of samples , each of which has surfaces with different angles of inclination with respect to the horizontal plane, and whose surfaces to be measured have different angles of inclination ,
each of the plurality of samples is a modeled object previously created by a modeling apparatus;
The parameter storage unit, as the parameter,
a reflection state parameter, which is a parameter indicating how light is reflected by a surface;
storing an uneven state parameter, which is a parameter indicating the state of unevenness formed on the surface of the surface, in association with the inclination angle of the surface;
In addition, by storing the reflection state parameter and the unevenness state parameter measured for each of the plurality of samples whose surfaces to be measured have different tilt angles, it is possible to correspond to the tilt angles of the surfaces. to store the reflective state parameter and the uneven state parameter;
The image generation device, wherein the image generation unit generates a computer graphics image representing the planned object based on the three-dimensional data, the reflection state parameter, and the uneven state parameter. The image generation unit determines how light is reflected and the unevenness at each position based on the reflection state parameter and the unevenness state parameter corresponding to the inclination angle of the surface at each position constituting the surface of the planned object. 2. The image generation device according to claim 1, wherein the computer graphics image is generated so as to represent the state of The parameter storage unit
storing BRDF information, which is information obtained by performing BRDF measurements on the plurality of samples, as the reflection state parameter;
3. The method according to claim 1, wherein normal information obtained by measuring a normal direction of each position of the surfaces of the plurality of samples is stored as the uneven state parameter. image production device. The image generator is
performing bump mapping on each position constituting the surface of the planned object based on the normal line information corresponding to the inclination angle of the surface at each position;
4. The image generating apparatus according to claim 3, wherein the BRDF is set based on the BRDF information corresponding to the inclination angle of the surface at each position. An image for generating a computer graphics image representing a planned object, which is an object to be modeled by a modeling apparatus that models a modeled object by laminating layers of modeling materials, based on three-dimensional data representing the planned object to be modeled. a generator,
a parameter storage unit for storing parameters used for expressing the state of the surface constituting the planned object with a computer graphics image;
an image generation unit that generates a computer graphics image showing the planned object;
a reception unit that receives an instruction from a user specifying the orientation of the planned object to be displayed in the computer graphics image;
a display unit that displays the computer graphics image generated by the image generation unit;
with
The parameters are obtained by measuring a plurality of samples, each having surfaces with different angles of inclination with respect to the horizontal plane,
each of the plurality of samples is a modeled object previously created by a modeling apparatus;
The parameter storage unit, as the parameter,
a reflection state parameter, which is a parameter indicating how light is reflected by a surface;
an uneven state parameter, which is a parameter indicating the state of unevenness formed on the surface of the surface;
is associated with the inclination angle of the face and stored,
The image generation unit generates a computer graphics image showing the planned object based on the three-dimensional data, the reflection state parameter, and the uneven state parameter,
When the reception unit receives an instruction to change the orientation of the planned object,
The image generating unit generates a computer graphics image showing the planned object in the changed orientation,
The image generating apparatus, wherein the display unit displays a computer graphics image showing the planned object in the orientation after the change. 6. The image according to claim 5, wherein the reception unit further receives an instruction from the user to specify the orientation of the planned object in the computer graphics image displayed on the display unit as the orientation during modeling. generator. further comprising a modeling data generation unit that generates modeling data representing the modeled object in a state in which an orientation at the time of modeling is specified;
7. The image generating apparatus according to claim 5, wherein the modeling data generation unit generates the modeling data based on the orientation during modeling specified by the user. An image for generating a computer graphics image representing a planned object, which is an object to be modeled by a modeling apparatus that models a modeled object by laminating layers of modeling materials, based on three-dimensional data representing the planned object to be modeled. a generator,
a parameter storage unit for storing parameters used for expressing the state of the surface constituting the planned object with a computer graphics image;
an image generation unit that generates a computer graphics image showing the planned object;
a lamination fringe prediction unit that predicts the occurrence of lamination fringes, which are striped patterns generated by laminating the layers of the modeling material ;
with
The parameters are obtained by measuring a plurality of samples, each having surfaces with different angles of inclination with respect to the horizontal plane,
each of the plurality of samples is a modeled object previously created by a modeling apparatus;
The parameter storage unit, as the parameter,
a reflection state parameter, which is a parameter indicating how light is reflected by a surface;
an uneven state parameter, which is a parameter indicating the state of unevenness formed on the surface of the surface;
is associated with the inclination angle of the face and stored,
The image generation unit generates a computer graphics image showing the planned object based on the three-dimensional data, the reflection state parameter, and the uneven state parameter,
The lamination fringe predicting unit, based on the three-dimensional data, the reflection state parameter, and the irregularity state parameter, is a region in which the lamination fringes occur that satisfies a criterion set in advance at the time of modeling of the object corresponding to the planned object. is predicted and notified to the user. further comprising a reception unit that receives a designation of a partial area in the planned object from a user;
9. The image generating apparatus according to claim 8, wherein the lamination fringe predicting unit predicts the state of the lamination fringes occurring in the partial region designated by the user. The lamination fringe prediction unit further predicts a state of lamination fringes that will occur on a surface that constitutes the partial region when the orientation of the planned object displayed in the computer graphics image is changed, and 10. The image generation apparatus according to claim 9, wherein the orientation of the planned object that makes stripes less conspicuous is presented to the user. further comprising a modeling data generation unit that generates modeling data representing the modeled object in a state in which an orientation at the time of modeling is specified;
The modeling data generation unit determines the orientation of the modeled object at the time of the modeling based on the manner of generation of the lamination fringes predicted by the lamination fringe prediction unit, and generates the modeling data. 11. The image generation device according to any one of claims 8 to 10. An image for generating a computer graphics image representing a planned object, which is an object to be modeled by a modeling apparatus that models a modeled object by laminating layers of modeling materials, based on three-dimensional data representing the planned object to be modeled. A method of generating,
a parameter storage step of storing, in a parameter storage unit, parameters used for expressing the state of the surface constituting the planned object in a computer graphics image;
an image generating step of generating a computer graphics image showing the planned object,
The parameters are obtained by measuring a plurality of samples , each of which has surfaces with different angles of inclination with respect to the horizontal plane, and whose surfaces to be measured have different angles of inclination ,
each of the plurality of samples is a modeled object previously created by a modeling apparatus;
The parameter storage unit, as the parameter,
a reflection state parameter, which is a parameter indicating how light is reflected by a surface;
storing an uneven state parameter, which is a parameter indicating the state of unevenness formed on the surface of the surface, in association with the inclination angle of the surface;
In addition, by storing the reflection state parameter and the unevenness state parameter measured for each of the plurality of samples whose surfaces to be measured have different tilt angles, it is possible to correspond to the tilt angles of the surfaces. to store the reflective state parameter and the uneven state parameter;
An image generating method, wherein in the image generating step, a computer graphics image representing the planned object is generated based on the three-dimensional data, the reflection state parameter, and the uneven state parameter. a sample preparation step of preparing the plurality of samples;
13. The image generation method according to claim 12, further comprising a parameter acquisition step of acquiring the reflection state parameter and the unevenness state parameter by performing measurements on the plurality of samples.

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