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WO2018196304A1 - Procédé et appareil de reconstruction d'image tridimensionnelle sur la base d'une séquence de debruijn - Google Patents

Procédé et appareil de reconstruction d'image tridimensionnelle sur la base d'une séquence de debruijn Download PDF

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Publication number
WO2018196304A1
WO2018196304A1 PCT/CN2017/107277 CN2017107277W WO2018196304A1 WO 2018196304 A1 WO2018196304 A1 WO 2018196304A1 CN 2017107277 W CN2017107277 W CN 2017107277W WO 2018196304 A1 WO2018196304 A1 WO 2018196304A1
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image
coded
binarized image
sequence
feature points
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Chinese (zh)
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WO2018196304A9 (fr
Inventor
刘晓利
王若曦
彭翔
蔡泽伟
汤其剑
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Shenzhen University
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Shenzhen University
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding

Definitions

  • the present invention relates to the field of three-dimensional image reconstruction technology, and in particular, to a three-dimensional image reconstruction method and apparatus based on a DeBruijn sequence.
  • the commonly used three-dimensional image reconstruction technology is a structured light three-dimensional image reconstruction technology
  • the structured light three-dimensional image reconstruction technology mainly falls into two categories: spatial domain coding and time domain coding, wherein the spatial domain coding often only needs to project a pattern.
  • the codeword of each point in the pattern can be obtained according to the information of neighboring points around it (such as pixel, color and geometric information, etc.), but it is interfered by information such as pixels and colors during the decoding stage, which has noise interference, thus affecting decoding. Robustness.
  • the existing three-dimensional image reconstruction method has poor noise resistance and poor robustness.
  • the main object of the present invention is to provide a three-dimensional image reconstruction method and apparatus based on DeBruijn sequence, which aims to solve the technical problem of poor anti-noise ability and poor robustness existing in the existing three-dimensional image reconstruction method.
  • a first aspect of the present invention provides a three-dimensional image reconstruction method based on a DeBruijn sequence, the method comprising:
  • the image of the coded template is projected onto the surface of the object, image acquisition is performed, and a coded image including the coded template image information and the object information is obtained, and the coded image is binarized to obtain a first binarized image, wherein
  • the first binarized image includes a plurality of coded feature points, each coded feature point including a central region;
  • a second aspect of the present invention provides a three-dimensional image reconstruction apparatus based on a DeBruijn sequence, the apparatus comprising:
  • a conversion module configured to perform binary conversion processing on the DeBruijn sequence to obtain a binary sequence, and sequentially fill the binary sequence in a gray area in a preset template image to obtain a coded template image;
  • An acquisition module configured to perform image acquisition after projecting the code template image onto an object surface, obtain a coded image including coded template image information and object information, and perform binarization processing on the coded image to obtain a first binarization An image, wherein the first binarized image comprises a plurality of coded feature points, each coded feature point comprising a central region;
  • a first determining module configured to determine location information of a central area of each of the encoded feature points based on the first binarized image
  • a second determining module configured to determine, according to the first binarized image and location information of each of the central regions, an encoded value of each of the encoded feature points, and perform three-dimensional image reconstruction by using the encoded value.
  • the present invention provides a three-dimensional image reconstruction method based on DeBruijn sequence.
  • a 4-level DeBruijn sequence is generated by using a shift register, and a binary sequence is obtained by performing a binary conversion process on the DeBruijn sequence, and the binary sequence is sequentially filled in the order.
  • the coded template image is obtained, and the coded template image is projected onto the surface of the object to perform image acquisition, and the coded image including the coded template image information and the object information is obtained, and the coded image is binarized to obtain a first binarized image, wherein the first binarized image includes a plurality of coded feature points, each coded feature point includes a central region, and position information of a central region of each coded feature point is determined based on the first binarized image Determining the coded value of each coded feature point based on the first binarized image and the position information of each central region, and performing three-dimensional image reconstruction using the coded value.
  • the embodiment of the present invention is based on the DeBruijn sequence.
  • Encoding the encoded template image obtained by encoding to Image acquisition is performed on the surface of the object to obtain a coded image, and the coded image is binarized.
  • the binarization process can overcome the color interference of the surface of the object, and the reconstruction of the three-dimensional image has higher anti-noise ability and better. Robustness.
  • FIG. 1 is a schematic flowchart of a method for reconstructing a three-dimensional image based on a DeBruijn sequence according to a first embodiment of the present invention
  • FIG. 3 is a schematic flow chart showing a refinement step of performing a binary conversion process on a DeBruijn sequence in step S102 in FIG. 1 to obtain a binary sequence;
  • FIG. 4 is a schematic diagram of conversion processing of a binary sequence by performing a binary conversion process on a DeBruijn sequence
  • Figure 5 is a first binarized image
  • step S104 is a schematic flow chart of the refinement step of step S104;
  • Figure 7 is a structural view of a peripheral area
  • step S105 is a schematic flow chart of the refinement step of step S105;
  • Figure 9 is a structural diagram of coded feature points
  • FIG. 10 is a schematic diagram of functional modules of a three-dimensional image reconstruction apparatus based on a DeBruijn sequence according to a second embodiment of the present invention.
  • FIG. 11 is a schematic diagram of a refinement function module of the conversion module 1002 of FIG. 10;
  • FIG. 12 is a schematic diagram of a refinement function module of the first determining module 1004;
  • FIG. 13 is a schematic diagram of a refinement function module of the second determining module 1005.
  • FIG. 1 is a schematic flowchart of a method for reconstructing a three-dimensional image based on a DeBruijn sequence according to a first embodiment of the present invention, including:
  • Step S101 generating a 4-level 2-level DeBruijn sequence by using a shift register
  • the 4-bit 2-level DeBruijn sequence is generated by using the shift register, and the DeBruijn sequence is generated by first determining the first sub-sequence by using the shift register, obtaining the iterative function by using the original polynomial, and iterating by using the iterative function. The operation generates a subsequent subsequence, and the iteration ends when the current subsequence is identical to the first subsequence, and a 4-ary 2-level DeBruijn sequence is obtained.
  • the 4-level 2-level DeBruijn sequence is a pseudo-random sequence with 4 elements, a total length of 16, an arbitrary length, and no sub-sequences.
  • the 4-level 2-level DeBruijn sequence element has a value of 0, 1. 2 and 3.
  • Step S102 performing a binary conversion process on the DeBruijn sequence to obtain a binary sequence, and sequentially filling the binary sequence in the gray region in the preset template image in order to obtain a coded template image;
  • the preset template image shown in FIG. 2 is a black and white checkerboard pattern, and the gray area 203 to be filled is set around each corner point, and the gray area is The area of 203 should be smaller than the area of the black checkerboard area 202 and the area of the white checkerboard area 201.
  • the binary sequence is sequentially filled in the gray area in the preset template image to obtain a coded template image.
  • the preset template image shown in FIG. 2 has a total of 7 rows of gray areas 203 to be filled, and each line has The gray area 203 of the seven grids, assuming that the first line binary sequence is 1100110, the first line binary sequence 1100110 is sequentially filled in order in the first gray line 203 of the preset template image to be filled in the gray area 203, the binary sequence The code word 1 in 1100110 causes the gray area 203 to become black, and the code word 0 in the binary sequence 1100110 causes the gray area 203 to become white, and the color of the 7 gray areas 203 after the first line is filled is displayed in black and white.
  • White black and white according to the above method, all the binary sequences are sequentially filled in the preset template image in order, and the encoded template image is obtained.
  • FIG. 3 is a schematic flowchart of a refinement step of performing binary conversion processing on the DeBruijn sequence in step S102 in FIG. 1 to obtain a binary sequence, including:
  • Step S301 converting each codeword in the DeBruijn sequence into binary numbers distributed up and down, and arranging them into two upper and lower rows;
  • step S302 the binary numbers of the even columns of all the binary numbers arranged in the upper and lower two rows are up-and-down changed to obtain a binary sequence.
  • FIG. 4 is a schematic diagram of a conversion process of a binary sequence obtained by performing a binary conversion process on a DeBruijn sequence, where the 4-element 2-level DeBruijn sequence element takes values of 0, 1, 2, and 3, corresponding to The binary numbers are 00, 01, 10, and 11, respectively.
  • each codeword in the row DeBruijn sequence 401 is converted into a binary number distributed up and down, and arranged in two rows.
  • the binary numbers of the even columns of all the binary numbers arranged in the upper and lower two rows are up-and-down shifted to obtain a binary sequence as shown by 403.
  • Step S103 After the code template image is projected onto the surface of the object, the image is collected, and the coded image including the coded template image information and the object information is obtained, and the coded image is binarized to obtain the first binarized image, wherein the first image is obtained.
  • the binarized image includes a plurality of coded feature points, each coded feature point including a central region;
  • the first binarized image includes a plurality of coded feature points, each coded feature point includes a central region, and some coded feature points include a center.
  • the color of the area is black, such as 501, and some of the coded feature points include a central area whose color is white, such as 502.
  • Step S104 Determine location information of a central region of each of the encoded feature points based on the first binarized image
  • FIG. 6 is a schematic flowchart of the refinement step of step S104, including:
  • Step S601 performing a closing operation on the first binarized image, and removing a peripheral region of each of the encoded feature points to obtain a second binarized image;
  • Step S602 determining location information of a central region in which the color in the second binarized image is black
  • Step S603 performing black-and-white inversion processing on each pixel in the first binarized image, and performing a closed operation on the first binarized image subjected to the black-and-white inversion processing to remove the peripheral region of each of the encoded feature points.
  • Step S604 determining that the color in the third binarized image is the position information of the black central region.
  • each of the coded feature points includes four peripheral regions.
  • the four peripheral regions are 701, 702, 703, and 704, respectively, and the first binarized image is closed and removed.
  • a second binarized image is obtained for each peripheral region of the encoded feature point, and the position information of the central region of the black color in the second binarized image is determined, because only the central region of the black color can be closed. Therefore, in order to determine the position information of the central region of the color in the first binarized image, first, each pixel in the first binarized image is subjected to black and white inversion processing, and the black and white inversion processing is performed.
  • a binarized image is subjected to a closing operation to remove a peripheral region of each of the encoded feature points to obtain a third binarized image, and the position information of the central region in which the color in the third binarized image is black is determined, and the third binary value is obtained.
  • the position information of the central region in which the color in the image is black is the position information of the central region in which the color in the first binarized image is white, thereby determining the first binarization map. All the position information in the central region.
  • Step S105 Determine an encoding value of each coding feature point based on the first binarized image and position information of each central region, and perform three-dimensional image reconstruction using the encoded value.
  • FIG. 8 is a schematic flowchart of the refinement step of step S105, including:
  • Step S801 determining four adjacent central regions having the same color as the current central region based on the first binarized image and the position information of the current central region;
  • Step S802 connecting the current central area and the four adjacent central areas to obtain four peripheral areas on the connection line;
  • Step S803 calculating gray values of the four peripheral regions, and using the gray value of the four peripheral regions as the encoded value of the encoded feature points corresponding to the current central region.
  • the current central area is 901, and based on the first binarized image and the position information of the current central area 901, four adjacent central areas having the same color as the current central area are determined to be 902, respectively.
  • 903, 904, and 905 connecting the current central area and four adjacent central areas, obtaining four peripheral areas on the connecting line, and four peripheral areas are 906, 907, 908, and 909, and calculating gray values of four peripheral areas.
  • the color of 906 is black, the gray value of 906 is 1, and the color of 907 is white, then the gray value of 907 is 0, the color of 908 is white, and the gray value of 908 is 0.
  • the gradation value of 909 is 0, and the gradation values 1, 0, 0, and 0 of the four peripheral regions are used as the coding values of the coding feature points corresponding to the current central region, that is, the current central region.
  • the coded value of the corresponding coded feature point is 1, 0, 0, 0.
  • the embodiment of the present invention performs encoding based on the DeBruijn sequence, which can effectively avoid the singularity of the encoding, and image the encoded template image obtained by encoding onto the surface of the object for image acquisition.
  • the coded image is obtained, and the coded image is binarized.
  • the binarization process can overcome the color interference of the surface of the object, and the reconstruction of the three-dimensional image has higher anti-noise ability and better robustness.
  • FIG. 10 is a schematic diagram of functional modules of a three-dimensional image reconstruction apparatus based on a DeBruijn sequence according to a second embodiment of the present invention, including:
  • a generating module 1001 configured to generate a 4-ary 2-level DeBruijn sequence by using a shift register
  • the generating module 1001 generates a 4-level 2-level DeBruijn sequence by using a shift register, and the method for generating the DeBruijn sequence is: first, the first sub-sequence is determined by using the shift register, the iterative function is obtained by using the original polynomial, and the iteration is utilized. The function performs an iterative operation to generate a subsequent subsequence. When the current subsequence is identical to the first subsequence, the iteration ends, and a 4-level 2-level DeBruijn sequence is obtained.
  • the 4-level 2-level DeBruijn sequence is a pseudo-random sequence with 4 elements, a total length of 16, an arbitrary length, and no sub-sequences.
  • the 4-level 2-level DeBruijn sequence element has a value of 0, 1. 2 and 3.
  • the conversion module 1002 is configured to perform a binary conversion process on the DeBruijn sequence to obtain a binary sequence, and sequentially fill the binary sequence in a gray area in the preset template image to obtain a coded template image;
  • the preset template image shown in FIG. 2 is a black and white checkerboard pattern, and the gray area 203 to be filled is set around each corner point, and the gray area is The area of 203 should be smaller than the area of the black checkerboard area 202 and the area of the white checkerboard area 201.
  • the conversion module 1002 sequentially fills the binary sequence in the gray area in the preset template image to obtain a coded template image.
  • the preset template image shown in FIG. 2 has a total of 7 rows of gray areas 203 to be filled. Each row has a gray area 203 of 7 grids. Assuming that the first line binary sequence is 1100110, the first line binary sequence 1100110 is sequentially filled in order in the first gray line 203 of the preset template image to be filled.
  • the code word 1 in the binary sequence 1100110 causes the gray area 203 to become black, and the code word 0 in the binary sequence 1100110 causes the gray area 203 to become white, and the color of the 7 gray areas 203 after the first line is filled
  • all the binary sequences are sequentially filled in the preset template image in order, and the encoded template image is obtained.
  • FIG. 11 is a schematic diagram of a refinement function module of the conversion module 1002 of FIG. 10, including:
  • the converting unit 1101 is configured to convert each codeword in the DeBruijn sequence into binary numbers distributed up and down, and arrange the upper and lower two rows;
  • the permutation unit 1102 is configured to perform upper and lower positions on the binary numbers of the even columns among all the binary numbers arranged in the upper and lower two rows to obtain a binary sequence.
  • FIG. 4 is a schematic diagram of a conversion process of a binary sequence obtained by performing a binary conversion process on a DeBruijn sequence, where the 4-element 2-level DeBruijn sequence element takes values of 0, 1, 2, and 3, corresponding to The binary numbers are 00, 01, 10, and 11, respectively.
  • the conversion unit 1101 converts each codeword in the row DeBruijn sequence 401 into upper and lower distributed binary numbers, and arranges them up and down.
  • the permutation unit 1102 up-and-down the binary numbers of the even-numbered columns of all the binary numbers arranged in the upper and lower two rows to obtain a binary sequence as shown at 403.
  • the acquisition module 1003 is configured to perform image acquisition after projecting the code template image onto the surface of the object, obtain a coded image including the coded template image information and the object information, and perform binarization processing on the coded image to obtain a first binarized image, wherein
  • the first binarized image includes a plurality of coded feature points, each of the coded feature points including a central region;
  • the first binarized image includes a plurality of coded feature points, each coded feature point includes a central region, and some coded feature points include a center.
  • the color of the area is black, such as 501, and some of the coded feature points include a central area whose color is white, such as 502.
  • a first determining module 1004 configured to determine location information of a central area of each of the encoded feature points based on the first binarized image
  • FIG. 12 is a schematic diagram of the refinement function module of the first determining module 1004, including:
  • a first closing operation unit 1201 configured to perform a closing operation on the first binarized image, and remove a peripheral region of each of the encoded feature points to obtain a second binarized image
  • a first determining unit 1202 configured to determine location information of a central area in which the color in the second binarized image is black
  • the second closing operation unit 1203 is configured to perform black and white inversion processing on each pixel in the first binarized image, and perform a closing operation on the first binarized image subjected to the black and white inversion processing to remove each encoding. a peripheral region of the feature point to obtain a third binarized image;
  • the second determining unit 1204 is configured to determine location information of a central area in which the color in the third binarized image is black.
  • each of the coded feature points includes four peripheral regions.
  • the four peripheral regions are respectively 701, 702, 703, and 704, and the first closed operation unit 1201 pairs the first binarized image.
  • the first determining unit 1202 determines the position information of the central region of the black color in the second binarized image, because only The central region of the black color is closed, so in order to determine the position information of the central region in which the color in the first binarized image is white, the second closing operation unit 1203 firstly sets each of the first binarized images.
  • the pixel performs black and white inversion processing, and performs a closing operation on the first binarized image subjected to the black and white inversion processing, and the second closing unit 1203 removes the peripheral region of each of the encoded feature points to obtain a third binarized image.
  • Determining position information of a central region in which the color in the third binarized image is black, and the position information of the central region in which the color in the third binarized image is black is the first binary value
  • the color in the image is the position information of the white central region, and the second determining unit 1204 thus determines the position information of all the central regions in the first binarized image.
  • the second determining module 1005 is configured to determine an encoding value of each coding feature point based on the first binarized image and position information of each central region, and perform three-dimensional image reconstruction using the encoded value.
  • FIG. 13 is a schematic diagram of the refinement function module of the second determining module 1005, including:
  • the third determining unit 1301 is configured to determine, according to the first binarized image and the location information of the current central region, four adjacent central regions that are the same color as the current central region;
  • the connecting unit 1302 is configured to connect the current central area and the four adjacent central areas to obtain four peripheral areas on the connecting line;
  • the calculating unit 1303 is configured to calculate grayscale values of the four peripheral regions, and use the grayscale values of the four peripheral regions as the encoded values of the encoded feature points corresponding to the current central region.
  • the current central area is 901
  • the third determining unit 1301 determines four neighbors having the same color as the current central area based on the first binarized image and the position information of the current central area 901.
  • the central areas are 902, 903, 904 and 905, respectively.
  • the connecting unit 1302 connects the current central area and the four adjacent central areas, and obtains four peripheral areas on the connecting line, and the four peripheral areas are 906, 907, 908 and 909, and the calculation is performed.
  • the unit 1303 calculates the gradation values of the four peripheral regions. As shown in FIG. 9, the color of 906 is black, the gradation value of 906 is 1, and the color of 907 is white, and the gradation value of 907 is 0, 908.
  • the gradation value of 908 is 0, the color of 909 is white, and the gradation value of 909 is 0, and the gradation values 1, 0, 0, and 0 of the four peripheral regions are taken as the current central region.
  • the coded value of the coded feature point that is, the coded value of the coded feature point corresponding to the current central region is 1, 0, 0, 0.
  • the embodiment of the present invention performs encoding based on the DeBruijn sequence, which can effectively avoid the singularity of the encoding, and image the encoded template image obtained by encoding onto the surface of the object for image acquisition.
  • the coded image is obtained, and the coded image is binarized.
  • the binarization process can overcome the color interference of the surface of the object, and the reconstruction of the three-dimensional image has higher anti-noise ability and better robustness.
  • the disclosed apparatus and method may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the modules is only a logical function division.
  • there may be another division manner for example, multiple modules or components may be combined or Can be integrated into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or module, and may be electrical, mechanical or otherwise.
  • the modules described as separate components may or may not be physically separated.
  • the components displayed as modules may or may not be physical modules, that is, may be located in one place, or may be distributed to multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.
  • the above integrated modules can be implemented in the form of hardware or in the form of software functional modules.
  • the integrated modules if implemented in the form of software functional modules and sold or used as separate products, may be stored in a computer readable storage medium.
  • the technical solution of the present invention which is essential or contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product stored in a storage medium.
  • a number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention.
  • the foregoing storage medium includes: a U disk, a mobile hard disk, a read only memory (ROM, Read-Only) Memory, random access memory (RAM), disk or optical disk, and other media that can store program code.

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Abstract

L'invention concerne un procédé et un appareil permettant de reconstruire une image tridimensionnelle sur la base d'une séquence de DeBruijn. Ledit procédé consiste à : utiliser un registre à décalage pour générer une séquence DeBruijn à deux niveaux à quatre éléments (101) ; effectuer une conversion binaire sur la séquence DeBruijn afin d'obtenir des séquences binaires, puis remplir les séquences binaires dans une zone de gris d'une image de modèle prédéfinie de façon séquentielle afin d'obtenir une image de modèle codée (102) ; effectuer une collecte d'image après que l'image de modèle codée a été projetée sur une surface d'un objet afin d'obtenir une image codée comprenant des informations d'image de modèle codées et des informations d'objet, puis binariser l'image codée afin d'obtenir une première image binarisée, la première image binarisée comprenant une pluralité de points caractéristiques codés et chacun des points caractéristiques codés comprenant une zone centrale (103) ; d'après la première image binarisée, déterminer des informations de position concernant la zone centrale de chacun des points caractéristiques codés (104) ; et d'après la première image binarisée et les informations de position concernant chaque zone centrale, déterminer une valeur codée de chacun des points caractéristiques codés, puis utiliser la valeur codée pour une reconstruction d'image tridimensionnelle (105). Une meilleure capacité anti-bruit ainsi qu'une meilleure robustesse sont obtenues lorsque le procédé est utilisé pour une reconstruction d'image tridimensionnelle.
PCT/CN2017/107277 2017-04-28 2017-10-23 Procédé et appareil de reconstruction d'image tridimensionnelle sur la base d'une séquence de debruijn Ceased WO2018196304A1 (fr)

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103400366A (zh) * 2013-07-03 2013-11-20 西安电子科技大学 基于条纹结构光的动态场景深度获取方法
CN103776392A (zh) * 2006-11-21 2014-05-07 曼蒂斯影像有限公司 三维几何建模和三维视频内容创建
CN105069789A (zh) * 2015-08-05 2015-11-18 西安电子科技大学 基于编码网格模板的结构光动态场景深度获取方法
CN105357511A (zh) * 2015-12-08 2016-02-24 上海图漾信息科技有限公司 深度数据检测系统
CN107240135A (zh) * 2017-04-28 2017-10-10 深圳大学 基于DeBruijn序列的三维图像重建方法及装置

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5838428A (en) * 1997-02-28 1998-11-17 United States Of America As Represented By The Secretary Of The Navy System and method for high resolution range imaging with split light source and pattern mask
CA2302372A1 (fr) * 1997-09-18 1999-03-25 Heikki Berg Diversite dans le temps dans un systeme amrt
KR20020058608A (ko) * 2000-12-30 2002-07-12 오길록 컴퓨팅 장치에서 두 개의 비-스플라인 곡선이나 곡면의경계가 연속성을 갖도록 하기 위한 대수적 블렌딩 처리방법
US9030470B2 (en) * 2012-08-14 2015-05-12 Hong Kong Applied Science and Technology Research Institute Company Limited Method and system for rapid three-dimensional shape measurement

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103776392A (zh) * 2006-11-21 2014-05-07 曼蒂斯影像有限公司 三维几何建模和三维视频内容创建
CN103400366A (zh) * 2013-07-03 2013-11-20 西安电子科技大学 基于条纹结构光的动态场景深度获取方法
CN105069789A (zh) * 2015-08-05 2015-11-18 西安电子科技大学 基于编码网格模板的结构光动态场景深度获取方法
CN105357511A (zh) * 2015-12-08 2016-02-24 上海图漾信息科技有限公司 深度数据检测系统
CN107240135A (zh) * 2017-04-28 2017-10-10 深圳大学 基于DeBruijn序列的三维图像重建方法及装置

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