WO2020258445A1 - 实时双向结构光三维成像 - Google Patents

实时双向结构光三维成像 Download PDF

Info

Publication number
WO2020258445A1
WO2020258445A1 PCT/CN2019/098911 CN2019098911W WO2020258445A1 WO 2020258445 A1 WO2020258445 A1 WO 2020258445A1 CN 2019098911 W CN2019098911 W CN 2019098911W WO 2020258445 A1 WO2020258445 A1 WO 2020258445A1
Authority
WO
WIPO (PCT)
Prior art keywords
dimensional
point cloud
fringe pattern
coordinates
deformed fringe
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2019/098911
Other languages
English (en)
French (fr)
Inventor
刘凯
胡子阳
许斌
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sichuan University
Original Assignee
Sichuan University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Sichuan University filed Critical Sichuan University
Publication of WO2020258445A1 publication Critical patent/WO2020258445A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • G01B11/2433—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures for measuring outlines by shadow casting
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three-dimensional [3D] modelling for computer graphics

Definitions

  • This application relates to the technical field of data processing, and specifically to a real-time bidirectional structured light three-dimensional imaging method and device.
  • Phase Measuring Profilometry is a high-precision and fast structured light three-dimensional measurement technology, based on structured light to perform three-dimensional imaging and contour reconstruction of the measured object, so it is also called three-dimensional reconstruction technology. It is widely used in reverse engineering, industrial detection, pattern recognition and other fields. After obtaining the phase information of the object, it is particularly important to convert the phase information of the object into an accurate three-dimensional point cloud faster.
  • the existing real-time bidirectional structured light 3D imaging method first calculates the phase through the deformed fringe pattern, and then solves the corresponding 3D point cloud data through matrix pseudo-inverse, least square method and other equation techniques, which has low computational efficiency and low accuracy.
  • the purpose of the embodiments of the present application includes providing a real-time bidirectional structured light three-dimensional imaging method and device, which can improve the calculation efficiency of three-dimensional point cloud data and have high calculation accuracy.
  • the embodiment of the present application provides a three-dimensional reconstruction method, including:
  • the three-dimensional point cloud data of the target object is calculated.
  • the expression formula of the deformed fringe pattern is:
  • a x represents the level at the point with coordinates (x c , y c ) on the deformed fringe map
  • Direction modulation component A y represents the vertical modulation component at the point with coordinates (x c , y c ) on the deformed fringe pattern
  • ⁇ x represents the coordinate on the deformed fringe pattern as (x c , y c )
  • ⁇ y represents the vertical phase at the point with coordinates (x c , y c ) on the deformed fringe pattern
  • n denotes the index of the deformed fringe pattern
  • N denotes the deformed fringe
  • the phase information includes ⁇ x and ⁇ y ;
  • the method before projecting the preset fringe pattern onto the target object by the projection device to generate the modulated deformed fringe pattern, the method further includes:
  • the point cloud look-up table is constructed according to the camera calibration matrix, the projection device calibration matrix and the epipolar equation corresponding to each coordinate point.
  • the camera device and the projection device need to satisfy the right-left relationship; when the preset fringe pattern changes vertically, the camera The device and the projection device need to satisfy the up-down relationship.
  • the scanning direction of the imaging device includes horizontal scanning, vertical scanning, horizontal and vertical scanning.
  • the scanning mode of the imaging device includes sine wave, straight line, and gray code.
  • calculating the three-dimensional point cloud data of the target object according to the phase information and a pre-built point cloud look-up table includes:
  • the three-dimensional point cloud data of the target object is obtained.
  • calculation formula of the point cloud lookup table is:
  • (X w , Y w , Z w ) T is the transposition of the three-dimensional coordinates of the point with coordinates (x c , y c ) on the deformed fringe graph
  • (x p , y p ) is the projection space coordinate
  • W p is the horizontal resolution of the projection by the projection device
  • H p is the vertical resolution of the projection by the projection device.
  • calculation formula for calculating the three-dimensional coordinates corresponding to each of the two-dimensional coordinates is:
  • the preset fringe pattern is a grayscale image, including sinusoidal fringe patterns of different phases.
  • the three-dimensional point cloud data includes the three-dimensional point cloud coordinates of the target object.
  • the embodiment of the application discloses a three-dimensional reconstruction device, including:
  • the projection module is used to project the preset fringe pattern onto the target object through the projection device to generate a modulated deformed fringe pattern
  • the first obtaining module is configured to obtain the deformed fringe pattern and calculate the phase information of the deformed fringe pattern
  • the calculation module is used to calculate the three-dimensional point cloud data of the target object according to the phase information and a pre-built point cloud look-up table.
  • An embodiment of the application discloses a computer device, including a memory and a processor, the memory is used to store a computer program, and the processor runs the computer program to make the computer device execute part or all of the information disclosed in this application.
  • the embodiment of the present application discloses a computer-readable storage medium, which stores a computer program used to implement the three-dimensional reconstruction method provided in the present application.
  • FIG. 1 is a schematic flowchart of a real-time bidirectional structured light three-dimensional imaging method according to an embodiment of the application
  • FIG. 2 is a schematic diagram of the measurement of a deformed fringe pattern provided by an embodiment of the application
  • FIG. 3 is a schematic flowchart of a real-time bidirectional structured light three-dimensional imaging method provided by an embodiment of the application;
  • FIG. 4 is a schematic structural diagram of a real-time bidirectional structured light three-dimensional imaging device provided by an embodiment of the application;
  • FIG. 5 is a schematic structural diagram of another real-time bidirectional structured light three-dimensional imaging device provided by an embodiment of the application.
  • 310-projection module 320-first acquisition module; 330-calculation module; 331-coordinate calculation sub-module; 332-variable determination sub-module; 333-point cloud calculation sub-module; 340-second acquisition module; 350-third Acquisition module; 360-equation calculation module; 370-building module.
  • FIG. 1 is a schematic block diagram of a flow diagram of a real-time bidirectional structured light three-dimensional imaging (reconstruction) method according to an embodiment of the application.
  • the real-time bidirectional structured light three-dimensional imaging method includes:
  • S101 Project a preset fringe pattern onto a target object through a projection device to generate a modulated deformed fringe pattern.
  • FIG. 2 is a schematic diagram of a deformed fringe pattern measurement provided by an embodiment of the present application.
  • a camera device and a projection device are needed to obtain the deformed fringe pattern of the target object.
  • the setting positions of the camera device and the projection device are shown in Figure 2.
  • the preset fringe pattern is projected to the target through the projection device
  • the deformed fringe pattern modulated by the measured target object is obtained through the camera device.
  • the preset fringe image is a grayscale image, which is used to help users study the changing laws of image pixels in different blending modes, and discuss the characteristics of the blending modes and their differences and connections.
  • the preset deformed fringe patterns include sinusoidal fringe patterns of different phases, etc., which are not limited in the embodiment of the present application.
  • the change direction of the preset fringe pattern needs to meet the positional relationship between the imaging device and the projection device, assuming that the preset fringe pattern is If the horizontal direction changes, the camera device or projection device needs to meet the right-left relationship; assuming that the preset fringe pattern changes vertically, the camera device or projection device needs to meet the up-down relationship, otherwise the quality of the reconstructed 3D point cloud will be poor. It is even completely wrong.
  • the positional relationship between the imaging device and the projection device can be ignored, and the position condition of simultaneous scanning in two directions can be satisfied.
  • the deformed fringe pattern can be obtained by scanning by a camera device, and the scanning direction can be horizontal scanning, vertical scanning, horizontal and vertical scanning, etc., which is not limited in the embodiment of the present application.
  • S103 Calculate the three-dimensional point cloud data of the target object according to the phase information and the pre-built point cloud look-up table.
  • the three-dimensional point cloud data includes the three-dimensional point cloud coordinates of the target object, etc., which is not limited in the embodiment of the present application.
  • the preset fringe pattern is first projected onto the target object through the projection device to generate the modulated deformed fringe pattern, and then the deformed fringe pattern is obtained, and further, the corresponding deformed fringe pattern is calculated according to the deformed fringe pattern.
  • Phase information after calculating the phase information, calculate the three-dimensional point cloud data through the pre-built point cloud look-up table. It can be seen that implementing the real-time bidirectional structured light three-dimensional imaging method described in this embodiment can improve the calculation efficiency of the three-dimensional point cloud data, and the calculation accuracy is high.
  • FIG. 3 is a schematic block diagram of a flow diagram of a real-time bidirectional structured light three-dimensional imaging method according to another embodiment of the application.
  • the real-time bidirectional structured light three-dimensional imaging method includes:
  • S201 Acquire a scanned picture for constructing a point cloud look-up table through a camera device.
  • an object when constructing the point cloud look-up table, an object may be used as a target, a fringe pattern is projected to the object through a projection device, and then a deformed fringe pattern obtained by modulating the fringe pattern by the object is acquired by the camera device , The scanned image used to construct the point cloud look-up table obtained by the camera is the deformed fringe image.
  • S202 Acquire a camera calibration matrix corresponding to the camera device and a projection device calibration matrix corresponding to the projection device.
  • the camera calibration matrix corresponding to the camera device and the projection device calibration matrix corresponding to the projection device are pre-stored and can be directly acquired and used.
  • a, b, and c are the linear coefficients of the polar equation.
  • the linear coefficient can be calculated from the camera calibration matrix and the projection device calibration matrix.
  • S204 Construct a point cloud look-up table according to the camera calibration matrix, the projection device calibration matrix, and the epipolar equation corresponding to each coordinate point.
  • the point cloud lookup table Before calculating the three-dimensional point cloud data of the target object, it is necessary to construct a point cloud lookup table in advance.
  • constructing the point cloud lookup table first calculate each coordinate on the scanned image according to the scanned image obtained by the camera device. The epipolar equation corresponding to the point, and finally the point cloud look-up table is constructed according to the acquired camera calibration matrix, the projection device calibration matrix and the polar equation corresponding to each coordinate point. After the point cloud look-up table is constructed, it can be based on The point cloud look-up table reconstructs 3D point cloud data of any object.
  • the camera calibration matrix is a parameter matrix that describes the correspondence between the points on the picture captured by the camera and the points in the real three-dimensional space
  • the projection device calibration matrix describes the points on the image projected by the projection device and The parameter matrix of the correspondence between points on the real three-dimensional space.
  • both the camera calibration matrix and the projection device calibration matrix may be 3 ⁇ 4 matrices, which are pre-stored and are two pre-known matrices.
  • the coordinates of a point on the picture scanned by the camera device are (x c , y c ), and the three-dimensional coordinates of the point (x c , y c ) are (X w , Y w , Z w ), and the image projected by the projection device
  • the coordinates of the point are (x p , y p ), then the transformation equation between (x c , y c ) and (X w , Y w , Z w ) is:
  • M wc is the camera calibration matrix
  • M wp is the calibration matrix of the projection device.
  • the calculation formula of the point cloud lookup table is:
  • (X w , Y w , Z w ) T is the transposition of the three-dimensional coordinates of the point with coordinates (x c , y c ) on the deformed fringe graph
  • (x p , y p ) is the projection Spatial coordinates
  • W p is the horizontal resolution of the projection device
  • H p is the vertical resolution of the projection device.
  • the value of the point cloud lookup variable corresponding to the two-dimensional coordinates of each point in the deformed fringe image can be determined according to the point cloud lookup table.
  • eleven sub lookup tables about the point cloud lookup variables can be constructed, which are respectively Sub lookup table, Sub lookup table, Sub lookup table, Sub lookup table, Sub lookup table, Sub lookup table, Sub lookup table, Sub lookup table, Sub-lookup table and Child lookup table.
  • S205 Project the preset fringe pattern onto the target object through the projection device to generate a modulated deformed fringe pattern.
  • the preset fringe pattern can be projected to the target object along the horizontal and vertical directions in a sine mode through the projection device, and then the target object is captured by the camera device to modulate the deformation of the preset fringe pattern.
  • the fringe pattern, the expression formula of the obtained deformed fringe pattern is:
  • a x represents the horizontal modulation component at the point with coordinates (x c , y c ) on the deformed fringe map
  • a y represents the vertical modulation component at the point with coordinates (x c , y c ) on the deformed fringe pattern
  • ⁇ x represents the horizontal phase at the point with coordinates (x c , y c ) on the deformed fringe pattern
  • ⁇ y represents the vertical phase at the point of the coordinate (x c , y c ) on the deformed fringe pattern
  • n represents the index of the deformed fringe pattern
  • N represents the total number of the deformed fringe pattern.
  • the expression formula of the deformed fringe pattern can be obtained, which in turn facilitates the calculation of phase information.
  • step S205 the following steps are further included:
  • the phase information includes ⁇ x and ⁇ y .
  • the corresponding calculation formulas of ⁇ x and ⁇ y are:
  • the corresponding phase information can be calculated according to the deformed fringe pattern, and the phase information includes phase information corresponding to each point on the deformed fringe pattern with coordinates (x c , y c ).
  • ⁇ x represents the horizontal phase at the point with coordinates (x c , y c ) on the deformed fringe pattern
  • ⁇ y represents the vertical phase at the point with coordinates (x c , y c ) on the deformed fringe pattern
  • n represents The serial number index of the deformed fringe pattern
  • N represents the total number of deformed fringe patterns
  • It represents the brightness of the image scanned in the vertical direction at the point with coordinates (x c , y c ) on the deformed fringe map.
  • the coordinates (x c , y c ) of each point on the deformed fringe pattern can be determined according to the deformed fringe pattern.
  • S207 Calculate the projection space coordinates according to the phase information, and determine the point cloud search variable corresponding to each two-dimensional coordinate according to the two-dimensional coordinates of each point in the deformed fringe diagram and the pre-built point cloud look-up table.
  • the calculation formula for calculating the projection space coordinates according to the phase information is:
  • (x p , y p ) are the coordinates in the projected space
  • ⁇ x represents the horizontal phase at the point on the deformed fringe map with coordinates (x c , y c )
  • ⁇ y represents the coordinates on the deformed fringe map as (x c ,
  • W p is the horizontal resolution of the projection device
  • H p is the vertical resolution of the projection device.
  • the point cloud lookup table includes eleven sub lookup tables
  • the point cloud lookup table includes Sub lookup table, Sub lookup table, Sub lookup table, Sub lookup table, Sub lookup table, Sub lookup table, Sub lookup table, Sub-lookup table and Child lookup table.
  • the search variables include with
  • Sub-lookup table is equivalent to a The matrix of values, in determining the two-dimensional coordinates (2, 7) corresponding to When the value of Determine the value in the second row and seventh column in the matrix of values, which is the corresponding two-dimensional coordinate (2, 7)
  • the value of other point cloud search variables can be obtained in the same way.
  • step S207 the following steps are further included:
  • S208 Calculate the three-dimensional coordinates corresponding to each two-dimensional coordinate according to the point cloud search variables and the projection space coordinates corresponding to each two-dimensional coordinate.
  • the deformed fringe pattern can be obtained by scanning by a camera device, and the scanning direction can be horizontal scanning, vertical scanning, horizontal and vertical scanning, etc., which is not limited in the embodiment of the present application.
  • the calculation formula of the three-dimensional coordinate (X w , Y w , Z w ) T corresponding to each two-dimensional coordinate is calculated (3D coordinate calculation formula 1) is:
  • the imaging device acquires the deformed fringe pattern by scanning in the vertical direction
  • the calculation formula for the three-dimensional coordinates scanned in the vertical direction is:
  • the imaging device acquires the deformed fringe pattern by scanning in the horizontal direction
  • the three-dimensional coordinate calculation formula 3 is:
  • step S208 the following steps are further included:
  • S209 Obtain the three-dimensional point cloud data of the target object according to the three-dimensional coordinates corresponding to all the two-dimensional coordinates.
  • the three-dimensional point cloud data of the target object can be calculated based on the phase information and the pre-built point cloud look-up table.
  • FIG. 4 is a schematic block diagram of a real-time bidirectional structured light three-dimensional imaging device according to an embodiment of the application.
  • the real-time bidirectional structured light three-dimensional imaging device includes:
  • the projection module 310 is used for projecting a preset fringe pattern onto a target object through a projection device to generate a modulated deformed fringe pattern.
  • the expression formula of the deformed fringe pattern is:
  • a x represents the horizontal modulation component at the point with coordinates (x c , y c ) on the deformed fringe map
  • a y represents the vertical modulation component at the point with coordinates (x c , y c ) on the deformed fringe pattern
  • ⁇ x represents the horizontal phase at the point with coordinates (x c , y c ) on the deformed fringe pattern
  • ⁇ y represents the vertical phase at the point of the coordinate (x c , y c ) on the deformed fringe pattern
  • n represents the index of the deformed fringe pattern
  • N represents the total number of the deformed fringe pattern.
  • the first obtaining module 320 is configured to obtain the deformed fringe pattern and calculate the phase information of the deformed fringe pattern.
  • the phase information includes ⁇ x and ⁇ y ;
  • the calculation module 330 is configured to calculate the three-dimensional point cloud data of the target object according to the phase information and the pre-built point cloud look-up table.
  • the projection module first projects the preset fringe pattern onto the target object through the projection device to generate a modulated deformed fringe pattern, and then the first acquiring module acquires the deformed fringe pattern, and based on the deformed fringe pattern The corresponding phase information is calculated.
  • the calculation module calculates the three-dimensional point cloud data through the pre-built point cloud look-up table, which can improve the calculation efficiency of the three-dimensional point cloud data, and the calculation accuracy is high.
  • FIG. 5 is a schematic structural diagram of another real-time bidirectional structured light three-dimensional imaging device provided by an embodiment of the present application.
  • the real-time two-way structured light three-dimensional imaging device shown in FIG. 5 is optimized by the real-time two-way structured light three-dimensional imaging device shown in FIG. 6.
  • the real-time two-way structured light three-dimensional imaging device further includes:
  • the second acquisition module 340 is configured to acquire the scanned image for constructing the point cloud look-up table through the camera device before projecting the preset fringe pattern onto the target object through the projection device to generate the modulated deformed fringe pattern.
  • the third acquiring module 350 is configured to acquire the camera calibration matrix corresponding to the camera device and the projection device calibration matrix corresponding to the projection device.
  • the equation calculation module 360 is used to calculate the epipolar equation corresponding to each coordinate point on the scanned image.
  • the construction module 370 is used to construct a point cloud look-up table according to the camera calibration matrix, the projection device calibration matrix, and the epipolar equation corresponding to each coordinate point.
  • the calculation module 330 includes:
  • the coordinate calculation sub-module 331 is used to calculate the projection space coordinates according to the phase information.
  • the variable determination sub-module 332 is configured to determine the point cloud search variable corresponding to each two-dimensional coordinate according to the two-dimensional coordinates of each point in the deformed fringe diagram and a pre-built point cloud look-up table.
  • the coordinate calculation sub-module 331 is also used to calculate the three-dimensional coordinates corresponding to each two-dimensional coordinate according to the point cloud search variable and the projection space coordinate corresponding to each two-dimensional coordinate.
  • the point cloud calculation sub-module 333 is used to obtain the 3D point cloud data of the target object according to the 3D coordinates corresponding to all the 2D coordinates.
  • the calculation formula of the point cloud lookup table is:
  • (X w , Y w , Z w ) T is the transposition of the three-dimensional coordinates of the point with coordinates (x c , y c ) on the deformed fringe graph
  • (x p , y p ) is the projection Spatial coordinates
  • W p is the horizontal resolution of the projection device
  • H p is the vertical resolution of the projection device.
  • the calculation formula for calculating the three-dimensional coordinates corresponding to each two-dimensional coordinate is:
  • the implementation of the real-time bidirectional structured light three-dimensional imaging device described in this embodiment realizes that the calculation efficiency of the three-dimensional point cloud data can be improved, and the calculation accuracy is high.
  • this application also provides a computer device.
  • the computer device includes a memory and a processor.
  • the memory can be used to store a computer program.
  • the processor runs the computer program so that the computer device executes the above method or functions of each module in the above real-time bidirectional structured light three-dimensional imaging device.
  • the memory may include a storage program area and a storage data area, where the storage program area can store an operating system, an application program required by at least one function (such as a sound playback function, an image playback function, etc.), etc.; Use the created data (such as audio data, phone book, etc.).
  • the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.
  • This embodiment also provides a computer storage medium for storing the computer program used in the above-mentioned computer device.
  • each block in the flowchart or block diagram may represent a module, program segment, or part of the code, and the module, program segment, or part of the code contains one or more functions for realizing the specified logical function. Executable instructions. It should also be noted that in some alternative implementations, the functions marked in the block may also occur in a different order from the order marked in the drawings.
  • each block in the block diagram and/or flowchart, and the combination of the blocks in the block diagram and/or flowchart can be implemented by a dedicated hardware-based system that performs the specified functions or actions Or it can be realized by a combination of dedicated hardware and computer instructions.
  • the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist alone, or two or more modules may be integrated to form an independent part.
  • the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer readable storage medium.
  • the technical solution of this application essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program code .
  • the present application provides a real-time bidirectional structured light three-dimensional imaging method and device, which can improve the calculation efficiency of three-dimensional point cloud data and has the advantage of high calculation accuracy.

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Computer Graphics (AREA)
  • Geometry (AREA)
  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Processing Or Creating Images (AREA)

Abstract

一种实时双向结构光三维成像方法及装置，涉及数据处理技术领域。先通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图，然后再获取该变形条纹图，进一步地，根据该变形条纹图计算出相应的相位信息，在计算出相位信息之后，通过预先构建的点云查找表，计算出三维点云数据，能够提升三维点云数据的计算效率，计算精确度高。

Description

实时双向结构光三维成像
相关申请交叉引用
本申请要求于2019年06月27日提交中国专利局的申请号为201910570997.7、名称为“一种三维重建方法及装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及数据处理技术领域，具体而言，涉及一种实时双向结构光三维成像方法及装置。
背景技术
目前，相位测量轮廓术(Phase Measuring Profilometry,PMP)是一种高精度，快速的结构光三维测量技术，基于结构光对被测物体进行三维成像和轮廓重建，因此又被称为三维重建技术，广泛应用于逆向工程，工业检测，模式识别等领域。在获取到物体的相位信息后，将物体的相位信息速度较快地转化为精确的三维点云显得尤为重要。现有实时双向结构光三维成像方法先通过变形条纹图计算出相位后，再通过矩阵伪逆、最小二乘法以及其他方程技巧求解出相应的三维点云数据，计算效率低，精确度低。
发明内容
本申请实施例的目的包括提供一种实时双向结构光三维成像方法及装置，能够提升三维点云数据的计算效率，计算精确度高。
本申请实施例提供了一种三维重建方法，包括：
通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图；
获取所述变形条纹图，并计算所述变形条纹图的相位信息；
根据所述相位信息和预先构建的点云查找表，计算所述目标物体的三维点云数据。
可选地，所述变形条纹图的表示公式为：
Figure PCTCN2019098911-appb-000001
其中，
Figure PCTCN2019098911-appb-000002
表示所述变形条纹图上坐标为(x c，y c)的点处的水平方向扫描的图像亮度，
Figure PCTCN2019098911-appb-000003
表示所述变形条纹图上坐标为(x c，y c)的点处的垂直方向扫描的图像亮度，A x表示所述变形条纹图上坐标为(x c，y c)的点处的水平方向的调制分量，A y表示所述变形条纹图上坐标为(x c，y c)的点处的垂直方向的调制分量，Φ x表示所述变形条纹图上坐标为(x c，y c)的点处的水平相位，Φ y表示所述变形条纹图上坐标为(x c，y c)的点处的垂直相位，n表示所述变形条纹图的序号索引，N表示所述变形条纹图的总数量。
可选地，所述相位信息包括Φ x和Φ y；
计算Φ x和Φ y的计算公式为：
Figure PCTCN2019098911-appb-000004
可选地，在所述通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图之前，还包括：
通过摄像装置获取用于构建点云查找表的扫描图片；
获取所述摄像装置对应的摄像装置校准矩阵和所述投影装置对应的投影装置校准矩阵；
计算所述扫描图片上每个坐标点对应的极线方程；
根据所述摄像装置校准矩阵、所述投影装置校准矩阵和所述每个坐标点对应的极线方程构建所述点云查找表。
可选地，当所述预设条纹图是水平方向变化的时，则所述摄像装置和投影装置需要满足对左右关系；当所述预设条纹图是是垂直变化的时，则所述摄像装置和投影装置需要满足对上下关系。
可选地，所述摄像装置的扫描方向包括水平扫描、垂直扫描、水平和垂直两个方向扫描。
可选地，所述摄像装置的扫描模式包括正弦波、直线、灰度码。
可选地，根据所述相位信息和预先构建的点云查找表，计算所述目标物体的三维点云数据，包括：
根据所述相位信息计算投影空间坐标，并根据所述变形条纹图中各个点的二维坐标和预先构建的点云查找表，确定每个所述二维坐标对应的点云查找变量；
根据每个所述二维坐标对应的所述点云查找变量和所述投影空间坐标计算每个所述二维坐标对应的三维坐标；
根据所有所述二维坐标对应的三维坐标，得到所述目标物体的三维点云数据。
可选地，所述点云查找表的计算公式为：
Figure PCTCN2019098911-appb-000005
其中，
Figure PCTCN2019098911-appb-000006
和
Figure PCTCN2019098911-appb-000007
均为所述点云查找变量，(X w，Y w，Z w) T是所述变形条纹图上坐标为(x c，y c)的点的三维坐标的转置，(x p，y p)是所述投影空间坐标，W p是所述投影装置投影的水平分辨率，H p是所述投影装置投影的垂直分辨率。
可选地，所述计算每个所述二维坐标对应的三维坐标的计算公式为：
Figure PCTCN2019098911-appb-000008
可选地，所述预设条纹图是灰度图像，包括不同相位的正弦条纹图。
可选地，所述三维点云数据包括目标物体的三维点云坐标。
本申请实施例公开了一种三维重建装置，包括：
投影模块，用于通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图；
第一获取模块，用于获取所述变形条纹图，并计算所述变形条纹图的相位信息；
计算模块，用于根据所述相位信息和预先构建的点云查找表，计算所述目标物体的三维点云数据。
本申请实施例公开了一种计算机设备，包括存储器以及处理器，所述存储器用于存储计算机程序，所述处理器运行所述计算机程序以使所述计算机设备执行本申请公开的部分或者全部所述的三维重建方法。
本申请实施例公开了一种计算机可读存储介质，其存储有用于实现本申请提供的三维重建方法所用的计算机程序。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对本申请实施例中所需要使用的附图作简单地介绍，应当理解，以下附图仅示出了本申请的某些实施例，因此不应被看作是对范围的限定，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他相关的附图。
图1为本申请实施例提供的一种实时双向结构光三维成像方法的流程示意图；
图2为本申请实施例提供的变形条纹图测量示意图；
图3为本申请实施例提供的一种实时双向结构光三维成像方法的流程示意图；
图4为本申请实施例提供的一种实时双向结构光三维成像装置的结构示意图；
图5为本申请实施例提供的另一种实时双向结构光三维成像装置的结构示意图。
附图标号：
310-投影模块；320-第一获取模块；330-计算模块；331-坐标计算子模 块；332-变量确定子模块；333-点云计算子模块；340-第二获取模块；350-第三获取模块；360-方程计算模块；370-构建模块。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行描述。
应注意到：相似的标号和字母在下面的附图中表示类似项，因此，一旦某一项在一个附图中被定义，则在随后的附图中不需要对其进行进一步定义和解释。同时，在本申请的描述中，术语“第一”、“第二”等仅用于区分描述，而不能理解为指示或暗示相对重要性。
请参看图1，图1为本申请实施例提供的一种实时双向结构光三维成像(重建)方法的流程示意框图。如图1所示，该实时双向结构光三维成像方法包括：
S101、通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图。
本申请实施例中，请参阅图2，图2是本申请实施例提供的一种变形条纹图测量示意图。在进行三维重建时，需要通过一个摄像设备和一个投影设备以获取目标物体的变形条纹图，摄像设备和投影设备的设置位置如图2所示，先通过投影装置将预设条纹图投射到目标物体上，然后通过摄像装置获取被测目标物体调制的变形条纹图。
本申请实施例中，预设条纹图是灰度图像，用于帮助用户研究图像像素在不同混合模式下变化的规律，探讨混合模式的特点以及相互之间的区别和联系。预设变形条纹图包括不同相位的正弦条纹图等，对此本申请实施例不作限定。
本申请实施例中，如果扫描模式是条纹状的，例如：正弦波、直线、灰度码等，预设条纹图的变化方向需要满足摄像设备和投影设备的位置关系，假设预设条纹图是水平方向变化的，则摄像设备或者投影设备需要满足对左右关系；假设预设条纹图是垂直变化的，则摄像设备或者投影设备需要满足对上下关系，否则重建的三维点云质量会很差，甚至是完全错误的。通过保持摄像设备和投影设备之间的基线足够长，并沿着水平和垂直方向投射图案，则可以忽略摄像设备和投影设备之间的位置关系，进而可 以满足两个方向同时扫描的位置条件。
S102、获取变形条纹图，并计算变形条纹图的相位信息。
本申请实施例中，变形条纹图的获取可以通过摄像装置扫描获得，其扫描方向可以为水平扫描、垂直扫描、水平和垂直两个方向扫描等，对此本申请实施例不作限定。
S103、根据相位信息和预先构建的点云查找表，计算目标物体的三维点云数据。
本申请实施例中，三维点云数据包括目标物体的三维点云坐标等，对此本申请实施例不作限定。
在上述实现过程中，先通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图，然后再获取该变形条纹图，进一步地，根据该变形条纹图计算出相应的相位信息，在计算出相位信息之后，通过预先构建的点云查找表，计算出三维点云数据。可见，实施本实施例所描述的实时双向结构光三维成像方法，能够提升三维点云数据的计算效率，计算精确度高。
请参看图3，图3为本申请另一实施例提供的一种实时双向结构光三维成像方法的流程示意框图。如图3所示，该实时双向结构光三维成像方法包括：
S201、通过摄像装置获取用于构建点云查找表的扫描图片。
本申请实施例中，在构建点云查找表时，可以先以一个物体为目标，通过投影装置向该物体投射条纹图，然后再通过摄像装置获取物体对该条纹图进行调制得到的变形条纹图，则通过摄像装置获取的用于构建点云查找表的扫描图片即为该变形条纹图。
S202、获取摄像装置对应的摄像装置校准矩阵和投影装置对应的投影装置校准矩阵。
本申请实施例中，摄像装置对应的摄像装置校准矩阵和投影装置对应的投影装置校准矩阵为预先存储好的，可以直接获取并使用的。
S203、计算扫描图片上每个坐标点对应的极线方程。
本申请实施例中，根据对极几何可知，对于每一个坐标为(x c，y c)的点来说，都有唯一一条极线与之对应，则坐标为(x c，y c)的点对应的极线 方程的表示公式为：
ax p+by p+c＝0；
其中a、b、c为极线方程的直线系数。该直线系数可以由摄像装置校准矩阵和投影装置校准矩阵计算得到。
S204、根据摄像装置校准矩阵、投影装置校准矩阵和每个坐标点对应的极线方程构建点云查找表。
在上述实现过程中，在计算目标物体的三维点云数据之前，需要预先构建点云查找表，在构建点云查找表时，先根据摄像装置获取的扫描图片，计算该扫描图片上每个坐标点对应的极线方程，最后再根据获取到的摄像装置校准矩阵、投影装置校准矩阵和每个坐标点对应的极线方程构建点云查找表，在构建了点云查找表之后，就可以根据该点云查找表重建任意物体的三维点云数据。
本申请实施例中，摄像装置校准矩阵是描述摄像装置捕捉回的图片上的点与真实三维空间上的点的对应关系的参数矩阵，投影装置校准矩阵是描述投影装置投射的图像上的点与真实三维空间上的点的对应关系的参数矩阵。
本申请实施例中，摄像装置校准矩阵和投影装置校准矩阵均可以为3×4矩阵，为预先存储好的，是预先已知的两个矩阵。设摄像装置扫描到的图片上点的坐标为(x c，y c)，点(x c，y c)对应的三维坐标为(X w，Y w，Z w)，投影装置投射的图像上点的坐标为(x p，y p)，则(x c，y c)与(X w，Y w，Z w)之间的变换方程为：
Figure PCTCN2019098911-appb-000009
Figure PCTCN2019098911-appb-000010
其中，
Figure PCTCN2019098911-appb-000011
M wc是摄像装置校准矩阵；
(x p，y p)与(X w，Y w，Z w)之间的转换公式以如下形式给出：
Figure PCTCN2019098911-appb-000012
Figure PCTCN2019098911-appb-000013
其中，
Figure PCTCN2019098911-appb-000014
M wp是投影装置校准矩阵。
本申请实施例中，点云查找表的计算公式为：
Figure PCTCN2019098911-appb-000015
其中，
Figure PCTCN2019098911-appb-000016
和
Figure PCTCN2019098911-appb-000017
均为点云查找变量，(X w，Y w，Z w) T是变形条纹图上坐标为(x c，y c)的点的三维坐标的转置，(x p，y p)是投影空间坐标，W p是投影装置投影的水平分辨率，H p是投影装置投影的垂直分辨率。
在上述实现过程中，在计算目标物体三维点云数据时，可以根据点云查找表确定出变形条纹图中各个点的二维坐标对应的点云查找变量的值。
本申请实施例中，根据上述点云查找表的计算公式，可以构建关于点云查找变量的十一个子查找表，分别为
Figure PCTCN2019098911-appb-000018
子查找表、
Figure PCTCN2019098911-appb-000019
子查找表、
Figure PCTCN2019098911-appb-000020
子查找表、
Figure PCTCN2019098911-appb-000021
子查找表、
Figure PCTCN2019098911-appb-000022
子查找表、
Figure PCTCN2019098911-appb-000023
子查找表、
Figure PCTCN2019098911-appb-000024
子查找表、
Figure PCTCN2019098911-appb-000025
子查找表、
Figure PCTCN2019098911-appb-000026
子查找表、
Figure PCTCN2019098911-appb-000027
子查找表和
Figure PCTCN2019098911-appb-000028
子查找表。
S205、通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图。
作为一种可选的实施方式，可以通过投影装置采用正弦模式沿水平和垂直两个方向将预设条纹图投射至目标物体，然后再通过摄像装置捕获目 标物体对该预设条纹图调制的变形条纹图，得到的变形条纹图的表示公式为：
Figure PCTCN2019098911-appb-000029
其中，
Figure PCTCN2019098911-appb-000030
表示变形条纹图上坐标为(x c，y c)的点处的水平方向扫描的图像亮度，
Figure PCTCN2019098911-appb-000031
表示变形条纹图上坐标为(x c，y c)的点处的垂直方向扫描的图像亮度，A x表示变形条纹图上坐标为(x c，y c)的点处的水平方向的调制分量，A y表示变形条纹图上坐标为(x c，y c)的点处的垂直方向的调制分量，Φ x表示变形条纹图上坐标为(x c，y c)的点处的水平相位，Φ y表示变形条纹图上坐标为(x c，y c)的点处的垂直相位，n表示变形条纹图的序号索引，N表示变形条纹图的总数量。
在上述实现过程中，在得到变形条纹图之后，可以得到该变形条纹图的表示公式，进而有利于相位信息的计算。
在步骤S205之后，还包括以下步骤：
S206、获取变形条纹图，并计算变形条纹图的相位信息。
本申请实施例中，相位信息包括Φ x和Φ y。对于每一个坐标为(x c，y c)的点，其对应的Φ x和Φ y的计算公式为：
Figure PCTCN2019098911-appb-000032
在上述实现过程中，可以根据变形条纹图计算出相应的相位信息，该相位信息包括变形条纹图上每个坐标为(x c，y c)的点对应的相位信息。其中，Φ x表示变形条纹图上坐标为(x c，y c)的点处的水平相位，Φ y表示变形条纹图上坐标为(x c，y c)的点处的垂直相位，n表示变形条纹图的序号索引，N表示变形条纹图的总数量，
Figure PCTCN2019098911-appb-000033
表示变形条纹图上坐标为(x c，y c)的点处的水平方向扫描的图像亮度，
Figure PCTCN2019098911-appb-000034
表示变形条纹图上坐标为(x c，y c)的点处的垂直方向扫描的图像亮度。
本申请实施例中，在得到变形条纹图之后，则可以根据变形条纹图确 定出变形条纹图上各个点的坐标(x c，y c)。
S207、根据相位信息计算投影空间坐标，并根据变形条纹图中各个点的二维坐标和预先构建的点云查找表，确定每个二维坐标对应的点云查找变量。
本申请实施例中，根据相位信息计算投影空间坐标的计算公式为：
Figure PCTCN2019098911-appb-000035
其中，(x p，y p)为投影空间坐标，Φ x表示变形条纹图上坐标为(x c，y c)的点处的水平相位，Φ y表示变形条纹图上坐标为(x c，y c)的点处的垂直相位，W p是投影装置投影的水平分辨率，H p是投影装置投影的垂直分辨率。
本申请实施例中，点云查找表包括十一个子查找表，点云查找表包括
Figure PCTCN2019098911-appb-000036
子查找表、
Figure PCTCN2019098911-appb-000037
子查找表、
Figure PCTCN2019098911-appb-000038
子查找表、
Figure PCTCN2019098911-appb-000039
子查找表、
Figure PCTCN2019098911-appb-000040
子查找表、
Figure PCTCN2019098911-appb-000041
子查找表、
Figure PCTCN2019098911-appb-000042
子查找表、
Figure PCTCN2019098911-appb-000043
子查找表、
Figure PCTCN2019098911-appb-000044
子查找表、
Figure PCTCN2019098911-appb-000045
子查找表和
Figure PCTCN2019098911-appb-000046
子查找表。当需要确定二维坐标(x c，y c)对应的点云查找变量包括
Figure PCTCN2019098911-appb-000047
Figure PCTCN2019098911-appb-000048
和
Figure PCTCN2019098911-appb-000049
举例来说，当二维坐标(x c，y c)＝(2，7)，确定
Figure PCTCN2019098911-appb-000050
的值时，则在
Figure PCTCN2019098911-appb-000051
子查找表中确定出(2，7)对应的值，即为二维坐标(2，7)对应的
Figure PCTCN2019098911-appb-000052
的值。在实际应用中，
Figure PCTCN2019098911-appb-000053
子查找表相当于一个
Figure PCTCN2019098911-appb-000054
的值的矩阵，在确定二维坐标(2，7)对应的
Figure PCTCN2019098911-appb-000055
的值的时候，在
Figure PCTCN2019098911-appb-000056
的值的矩阵中确定出第2行第7列的值，即为二维坐标(2，7)对应的
Figure PCTCN2019098911-appb-000057
的值，其他点云查找变量的值同理可得。
在步骤S207之后，还包括以下步骤：
S208、根据每个二维坐标对应的点云查找变量和投影空间坐标计算每个二维坐标对应的三维坐标。
本申请实施例中，变形条纹图的获取可以通过摄像装置扫描获得，其扫描方向可以为水平扫描、垂直扫描、水平和垂直两个方向扫描等，对此本申请实施例不作限定。
本申请实施例中，当摄像装置通过水平和垂直两个方向扫描的方式获 取变形条纹图时，则计算每个二维坐标对应的三维坐标(X w，Y w，Z w) T的计算公式(三维坐标计算公式1)为：
Figure PCTCN2019098911-appb-000058
其中，
Figure PCTCN2019098911-appb-000059
和
Figure PCTCN2019098911-appb-000060
均为点云查找变量，(x p，y p)是投影空间坐标。
作为一种可选的实施方式，当摄像装置通过垂直方向扫描的方式获取变形条纹图时，则上述三维坐标计算公式1中，
Figure PCTCN2019098911-appb-000061
进而可得垂直方向扫描的三维坐标的计算公式(三维坐标计算公式2)为：
Figure PCTCN2019098911-appb-000062
其中，
Figure PCTCN2019098911-appb-000063
和
Figure PCTCN2019098911-appb-000064
均为点云查找变量，(x p，y p)是投影空间坐标。
作为一种可选的实施方式，当摄像装置通过水平方向扫描的方式获取变形条纹图时，则上述三维坐标计算公式1中，
Figure PCTCN2019098911-appb-000065
则可得水平方向扫描的三维坐标的计算公式(三维坐标计算公式3)为：
Figure PCTCN2019098911-appb-000066
其中，
Figure PCTCN2019098911-appb-000067
和
Figure PCTCN2019098911-appb-000068
均为点云查找变量，(x p，y p)是投影空间坐标。
在步骤S208之后，还包括以下步骤：
S209、根据所有二维坐标对应的三维坐标，得到目标物体的三维点云数据。
在上述实现过程中，在计算目标物体的三维点云数据时，先根据相位信息计算投影空间坐标并根据变形条纹图中各个点的二维坐标，确定每个所述二维坐标对应的点云查找变量，最后，再根据每个所述二维坐标对应的点云查找变量和投影空间坐标计算出每个二维坐标对应的三维坐标，进而得到目标物体的三维点云数据。
本申请实施例中，实施上述步骤S207～步骤S209，能够根据相位信息和预先构建的点云查找表，计算目标物体的三维点云数据。
可见，实施图3所描述的实时双向结构光三维成像方法，能够提升三维点云数据的计算效率，计算精确度高。
请参看图4，图4为本申请实施例提供的一种实时双向结构光三维成像装置的结构示意框图。如图4所示，该实时双向结构光三维成像装置包括：
投影模块310，用于通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图。
本申请实施例中，变形条纹图的表示公式为：
Figure PCTCN2019098911-appb-000069
其中，
Figure PCTCN2019098911-appb-000070
表示变形条纹图上坐标为(x c，y c)的点处的水平方向扫描的图像亮度，
Figure PCTCN2019098911-appb-000071
表示变形条纹图上坐标为(x c，y c)的点处的垂直方向扫描的图像亮度，A x表示变形条纹图上坐标为(x c，y c)的点处的水平方向的调制分量，A y表示变形条纹图上坐标为(x c，y c)的点处的垂直方向的调制分量，Φ x表示变形条纹图上坐标为(x c，y c)的点处的水平相位，Φ y表示变形条纹图上坐标为(x c，y c)的点处的垂直相位，n表示变形条纹图的序号索引，N表示变形条纹图的总数量。
第一获取模块320，用于获取变形条纹图，并计算变形条纹图的相位信息。
本申请实施例中，相位信息包括Φ x和Φ y；
计算Φ x和Φ y的计算公式为：
Figure PCTCN2019098911-appb-000072
计算模块330，用于根据相位信息和预先构建的点云查找表，计算目标物体的三维点云数据。
在上述实现过程中，投影模块先通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图，然后第一获取模块再获取该变形条纹图，并根据该变形条纹图计算出相应的相位信息，在计算出相位信息之后，计算模块通过预先构建的点云查找表，计算出三维点云数据，能够提升三维点云数据的计算效率，计算精确度高。
作为一种可选的实施方式，请参阅图5，图5是本申请实施例提供的另一种实时双向结构光三维成像装置的结构示意图。其中，图5所示的实时双向结构光三维成像装置是由图6所示的实时双向结构光三维成像装置进行优化得到的，如图5所示，该实时双向结构光三维成像装置还包括：
第二获取模块340，用于在通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图之前，通过摄像装置获取用于构建点云查找表的扫描图片。
第三获取模块350，用于获取摄像装置对应的摄像装置校准矩阵和投影装置对应的投影装置校准矩阵。
方程计算模块360，用于计算扫描图片上每个坐标点对应的极线方程。
构建模块370，用于根据摄像装置校准矩阵、投影装置校准矩阵和每个坐标点对应的极线方程构建点云查找表。
作为一种可选的实施方式，计算模块330包括：
坐标计算子模块331，用于根据相位信息计算投影空间坐标。
变量确定子模块332，用于根据变形条纹图中各个点的二维坐标和预先构建的点云查找表，确定每个二维坐标对应的点云查找变量。
坐标计算子模块331，还用于根据每个二维坐标对应的点云查找变量和投影空间坐标计算每个二维坐标对应的三维坐标。
点云计算子模块333，用于根据所有二维坐标对应的三维坐标，得到目 标物体的三维点云数据。
本申请实施例中，点云查找表的计算公式为：
Figure PCTCN2019098911-appb-000073
其中，
Figure PCTCN2019098911-appb-000074
和
Figure PCTCN2019098911-appb-000075
均为点云查找变量，(X w，Y w，Z w) T是变形条纹图上坐标为(x c，y c)的点的三维坐标的转置，(x p，y p)是投影空间坐标，W p是投影装置投影的水平分辨率，H p是投影装置投影的垂直分辨率。
本申请实施例中，计算每个二维坐标对应的三维坐标的计算公式为：
Figure PCTCN2019098911-appb-000076
在上述实现过程中，当要计算变形条纹图上坐标为(x c，y c)的点对应的三维坐标时，先计算投影空间坐标(x p，y p)，再根据查找表确定出(x c，y c)对应的点云查找变量，最后将投影空间坐标(x p，y p)和点云查找变量的值代入到上述三维坐标的计算公式中，进而可以计算出(x c，y c)对应的三维坐标(X w，Y w，Z w)，同理可得变形条纹图上所有点的三维坐标，进而得到目标物体的三维构建数据。
可见，实施本实施例描述的实时双向结构光三维成像装置，实现了能够提升三维点云数据的计算效率，计算精确度高。
此外，本申请还提供了一种计算机设备。该计算机设备包括存储器和 处理器，存储器可用于存储计算机程序，处理器通过运行计算机程序，从而使该计算机设备执行上述方法或者上述实时双向结构光三维成像装置中的各个模块的功能。
存储器可包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序(比如声音播放功能、图像播放功能等)等；存储数据区可存储根据移动终端的使用所创建的数据(比如音频数据、电话本等)等。此外，存储器可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他易失性固态存储器件。
本实施例还提供了一种计算机存储介质，用于储存上述计算机设备中使用的计算机程序。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置和方法，也可以通过其它的方式实现。以上所描述的装置实施例仅仅是示意性的，例如，附图中的流程图和框图显示了根据本申请的多个实施例的装置、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段或代码的一部分，所述模块、程序段或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现方式中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个连续的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或动作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
另外，在本申请各个实施例中的各功能模块可以集成在一起形成一个独立的部分，也可以是各个模块单独存在，也可以两个或两个以上模块集成形成一个独立的部分。
所述功能如果以软件功能模块的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储 介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述仅为本申请的实施例而已，并不用于限制本申请的保护范围，对于本领域的技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本申请的保护范围之内。应注意到：相似的标号和字母在下面的附图中表示类似项，因此，一旦某一项在一个附图中被定义，则在随后的附图中不需要对其进行进一步定义和解释。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应所述以权利要求的保护范围为准。
需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
工业实用性
本申请提供了一种实时双向结构光三维成像方法及装置，能够提升三维点云数据的计算效率，具有计算精确度高的优点。

Claims (15)

  1. 一种三维重建方法，其特征在于，包括：
    通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图；
    获取所述变形条纹图，并计算所述变形条纹图的相位信息；
    根据所述相位信息和预先构建的点云查找表，计算所述目标物体的三维点云数据。
  2. 根据权利要求1所述的三维重建方法，其特征在于，所述变形条纹图的表示公式为：
    Figure PCTCN2019098911-appb-100001
    其中，
    Figure PCTCN2019098911-appb-100002
    表示所述变形条纹图上坐标为(x c，y c)的点处的水平方向扫描的图像亮度，
    Figure PCTCN2019098911-appb-100003
    表示所述变形条纹图上坐标为(x c，y c)的点处的垂直方向扫描的图像亮度，A x表示所述变形条纹图上坐标为(x c，y c)的点处的水平方向的调制分量，A y表示所述变形条纹图上坐标为(x c，y c)的点处的垂直方向的调制分量，Φ x表示所述变形条纹图上坐标为(x c，y c)的点处的水平相位，Φ y表示所述变形条纹图上坐标为(x c，y c)的点处的垂直相位，n表示所述变形条纹图的序号索引，N表示所述变形条纹图的总数量。
  3. 根据权利要求1或2所述的三维重建方法，其特征在于，所述相位信息包括Φ x和Φ y；
    计算Φ x和Φ y的计算公式为：
    Figure PCTCN2019098911-appb-100004
  4. 根据权利要求1至3中任一项所述的三维重建方法，其特征在于，在所述通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图之前，还包括：
    通过摄像装置获取用于构建点云查找表的扫描图片；
    获取所述摄像装置对应的摄像装置校准矩阵和所述投影装置对应的投影装置校准矩阵；
    计算所述扫描图片上每个坐标点对应的极线方程；
    根据所述摄像装置校准矩阵、所述投影装置校准矩阵和所述每个坐标点对应的极线方程构建所述点云查找表。
  5. 根据权利要求4所述的三维重建方法，其特征在于，当所述预设条纹图是水平方向变化的时，则所述摄像装置和投影装置需要满足对左右关系；当所述预设条纹图是是垂直变化的时，则所述摄像装置和投影装置需要满足对上下关系。
  6. 根据权利要求4或5所述的三维重建方法，其特征在于，所述摄像装置的扫描方向包括水平扫描、垂直扫描、水平和垂直两个方向扫描。
  7. 根据权利要求4至6中任一项所述的三维重建方法，其特征在于，所述摄像装置的扫描模式包括正弦波、直线、灰度码。
  8. 根据权利要求1至7中任一项所述的三维重建方法，其特征在于，所述根据所述相位信息和预先构建的点云查找表，计算所述目标物体的三维点云数据，包括：
    根据所述相位信息计算投影空间坐标，并根据所述变形条纹图中各个点的二维坐标和预先构建的点云查找表，确定每个所述二维坐标对应的点云查找变量；
    根据每个所述二维坐标对应的所述点云查找变量和所述投影空间坐标计算每个所述二维坐标对应的三维坐标；
    根据所有所述二维坐标对应的三维坐标，得到所述目标物体的三维点云数据。
  9. 根据权利要求1至8中任一项所述的三维重建方法，其特征在于，所述点云查找表的计算公式为：
    Figure PCTCN2019098911-appb-100005
    其中，
    Figure PCTCN2019098911-appb-100006
    和
    Figure PCTCN2019098911-appb-100007
    均为所述点云查找变量，(X w，Y w，Z w) T是所述变形条纹图上坐标为(x c，y c)的点的三维坐标的转置，(x p，y p)是所述投影空间坐标，W p是所述投影装置投影的水平分辨率，H p是所述投影装置投影的垂直分辨率。
  10. 根据权利要求8或9所述的三维重建方法，其特征在于，所述计算每个所述二维坐标对应的三维坐标的计算公式为：
    Figure PCTCN2019098911-appb-100008
  11. 根据权利要求1至10中任一项所述的三维重建方法，其特征在于，所述预设条纹图是灰度图像，包括不同相位的正弦条纹图。
  12. 根据权利要求1至11中任一项所述的三维重建方法，其特征在于，所述三维点云数据包括目标物体的三维点云坐标。
  13. 一种三维重建装置，其特征在于，包括：
    投影模块，用于通过投影装置将预设条纹图投射到目标物体上，以产生调制后的变形条纹图；
    第一获取模块，用于获取所述变形条纹图，并计算所述变形条纹图的相位信息；
    计算模块，用于根据所述相位信息和预先构建的点云查找表，计算所 述目标物体的三维点云数据。
  14. 一种计算机设备，其特征在于，包括存储器以及处理器，所述存储器用于存储计算机程序，所述处理器运行所述计算机程序以使所述计算机设备执行权利要求1至12中任一项所述的三维重建方法。
  15. 一种计算机可读存储介质，其特征在于，其存储有用于实现权利要求1至12中任一项所述的三维重建方法时所使用的计算机程序。
PCT/CN2019/098911 2019-06-27 2019-08-01 实时双向结构光三维成像 Ceased WO2020258445A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201910570997.7 2019-06-27
CN201910570997.7A CN110310365B (zh) 2019-06-27 2019-06-27 一种三维重建方法及装置

Publications (1)

Publication Number Publication Date
WO2020258445A1 true WO2020258445A1 (zh) 2020-12-30

Family

ID=68077065

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/098911 Ceased WO2020258445A1 (zh) 2019-06-27 2019-08-01 实时双向结构光三维成像

Country Status (2)

Country Link
CN (1) CN110310365B (zh)
WO (1) WO2020258445A1 (zh)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN120580350A (zh) * 2025-05-19 2025-09-02 国网山东省电力公司宁津县供电公司 结构光投影变压器台架三维模型构建装置及方法

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111462331B (zh) * 2020-03-31 2023-06-27 四川大学 扩展对极几何并实时计算三维点云的查找表方法
CN111553985B (zh) * 2020-04-30 2023-06-13 四川大学 邻图配对式的欧式三维重建方法及装置
CN112562064B (zh) * 2020-12-08 2023-03-14 四川大学 一种三维点云的精度无损实时计算方法及系统
CN114114178B (zh) * 2021-12-10 2022-06-21 南京邮电大学 一种雷达和视频图像的校准装置
CN114663597B (zh) * 2022-04-06 2023-07-04 四川大学 基于归一化扩展极线几何的实时结构光重建方法及装置
CN114708316B (zh) * 2022-04-07 2023-05-05 四川大学 基于圆形条纹的结构光三维重建方法、装置和电子设备

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105953746A (zh) * 2016-05-16 2016-09-21 西安工业大学 动态物体的三维轮廓实时测量方法
CN106257995A (zh) * 2016-07-25 2016-12-28 深圳大学 一种结构光场三维成像方法及其系统
CN106767533A (zh) * 2016-12-28 2017-05-31 深圳大学 基于条纹投影轮廓术的高效相位‑三维映射方法及系统
KR20170119524A (ko) * 2016-04-19 2017-10-27 한국과학기술원 삼차원 영상 복원 장치 및 삼차원 영상 복원 방법

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105953747B (zh) * 2016-06-07 2019-04-02 杭州电子科技大学 结构光投影全视角三维成像系统及方法
KR102669967B1 (ko) * 2016-11-24 2024-05-29 삼성전자주식회사 홀로그램 생성 방법 및 홀로그램 생성 장치
WO2018105786A1 (ko) * 2016-12-08 2018-06-14 전자부품연구원 홀로그래픽 영상처리 장치 및 방법
CN107702663B (zh) * 2017-09-29 2019-12-13 五邑大学 一种基于具有标志点的旋转平台的点云配准方法
CN108955574B (zh) * 2018-07-09 2020-04-28 广东工业大学 一种三维测量方法及系统
CN109242957A (zh) * 2018-08-27 2019-01-18 深圳积木易搭科技技术有限公司 一种基于多重约束的单帧编码结构光三维重建方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20170119524A (ko) * 2016-04-19 2017-10-27 한국과학기술원 삼차원 영상 복원 장치 및 삼차원 영상 복원 방법
CN105953746A (zh) * 2016-05-16 2016-09-21 西安工业大学 动态物体的三维轮廓实时测量方法
CN106257995A (zh) * 2016-07-25 2016-12-28 深圳大学 一种结构光场三维成像方法及其系统
CN106767533A (zh) * 2016-12-28 2017-05-31 深圳大学 基于条纹投影轮廓术的高效相位‑三维映射方法及系统

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN120580350A (zh) * 2025-05-19 2025-09-02 国网山东省电力公司宁津县供电公司 结构光投影变压器台架三维模型构建装置及方法

Also Published As

Publication number Publication date
CN110310365A (zh) 2019-10-08
CN110310365B (zh) 2021-01-05

Similar Documents

Publication Publication Date Title
WO2020258445A1 (zh) 实时双向结构光三维成像
JP6394005B2 (ja) 投影画像補正装置、投影する原画像を補正する方法およびプログラム
CN111735439B (zh) 地图构建方法、装置和计算机可读存储介质
CN107564069A (zh) 标定参数的确定方法、装置及计算机可读存储介质
WO2022134328A1 (zh) 一种建筑信息模型的构建方法及装置
JP6598673B2 (ja) データ処理装置およびその方法
CN109089093A (zh) 图像处理方法、装置和设备
WO2015068470A1 (ja) ３次元形状計測装置、３次元形状計測方法及び３次元形状計測プログラム
TW201618039A (zh) 點雲邊界直角邊修補系統及方法
WO2018176440A1 (zh) 点云与平面图像融合方法、智能设备及非易失性计算机可读存储介质
Wilm et al. Accurate and simple calibration of DLP projector systems
CN115272110A (zh) 一种结构光三维重建中投影机畸变校正方法及装置
CN109781030B (zh) 基于点扩散函数估计的相位校正方法及装置
CN107170007B (zh) 具有图像散焦功能的图像装置及其产生散焦图像的方法
CN106767405B (zh) 相位映射辅助三维成像系统快速对应点匹配的方法及装置
CN113436269A (zh) 图像稠密立体匹配方法、装置和计算机设备
JP2018519733A5 (zh)
CN119048718B (zh) 一种增强现实三维注册的方法及电子设备
Ayaz et al. Multiview registration-based handheld 3D profiling system using visual navigation and structured light
KR101424118B1 (ko) 3차원 스캐닝 장치 및 3차원 스캐닝 방법
CN111462331A (zh) 扩展对极几何并实时计算三维点云的若干方法
CN113706692B (zh) 三维图像重构方法、装置、电子设备以及存储介质
KR20160052256A (ko) 가상 특징점을 이용하는 3차원 공간 매핑장치 및 그 방법
CN113375600B (zh) 一种三维测量方法、装置和电子设备
CN113421292A (zh) 一种三维建模细节增强方法及装置

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19935744

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 19935744

Country of ref document: EP

Kind code of ref document: A1

122 Ep: pct application non-entry in european phase

Ref document number: 19935744

Country of ref document: EP

Kind code of ref document: A1