CN110940295B - High-reflection object measurement method and system based on laser speckle limit constraint projection - Google Patents
High-reflection object measurement method and system based on laser speckle limit constraint projection Download PDFInfo
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Abstract
The high-reflection object measuring method and system based on laser speckle limit constraint projection can accurately finish the measurement of a high-reflection object only by simple laser emission and image acquisition equipment, have a simple structure, do not need to be coated with anti-reflection materials or adopt contact measurement, ensure that the measured object is not damaged, have certain universality for the measurement of common objects in industrial life, effectively reduce the influence caused by the reflected light of the high-reflection object, and improve the three-dimensional measurement precision of the reflection object. The method comprises the following steps: (1) constructing a camera mathematical model to obtain internal parameters and external parameters of the camera; (2) projecting strip-shaped speckles to the surface of a high-reflection object in the baseline direction of a camera, driving the object to move by a translation table, and acquiring a plurality of groups of pictures by the camera; (3) correcting by adopting a Fusiello limit correction method; (4) performing stereo matching, and solving the parallax of the left and right pictures to obtain a parallax map; (5) acquiring three-dimensional point cloud data; (6) the three-dimensional topography of the object is reconstructed.
Description
Technical Field
The invention relates to the technical field of optical three-dimensional measurement, in particular to a high-reflection object measurement method based on laser speckle limit constraint projection and a high-reflection object measurement system based on laser speckle limit constraint projection.
Background
In the field of three-dimensional measurement, the optical three-dimensional measurement technology has the advantages of non-contact measurement, high speed, high accuracy, high automation degree and the like, is widely applied to the fields of machine vision, reverse engineering, medical diagnosis, medical cosmetology, human body measurement, manufacturing industry and the like, and achieves great progress. However, in industry and daily life, a large number of high-reflection objects exist, such as ceramic products, metal parts and the like, the surface reflectivity of the objects to be measured has a large variation range, and the traditional optical three-dimensional measurement method is difficult to measure. Therefore, finding a high-precision and simple-structure measuring method for a high-reflection object is a problem which needs to be solved urgently in the field of three-dimensional measurement at the present stage.
In the existing optical three-dimensional measurement research method, phase measurement profilometry is one of the important methods for measuring the three-dimensional appearance of a diffuse reflection object, and the basic principle is as follows: the projection system projects phase-shift sine stripes to the measured object, the camera obtains the sine stripes deformed by the object, and the three-dimensional shape of the measured object is obtained through a unwrapping algorithm. In the method, phase interference caused by diffuse reflection on the surface of the object to be measured is the same in the two cameras, so that errors caused by the diffuse reflection can be eliminated, and the three-dimensional measurement of the object with the diffuse reflection on the surface is realized. However, when measuring objects having a high surface reflectivity or reflecting each other in the surface by using this method, the reflected light beams are mixed, and thus it is difficult to perform three-dimensional measurement of the highly reflective object by the phase profilometry.
In addition, the document 3D Shape and index application By Structured Light Transport (SLT) proposes a Structured Light transfer technique for measuring the three-dimensional topography of highly reflective objects. The technology only processes the optical domain, does not need subsequent calculation, and is a method for eliminating reflection by a physical device only outputting a real-time acquisition image through a specially set hardware device, so that the complexity of light transmission generated on the surface of a measured object can be ignored. The transmission process of light can be analyzed in a geometric mode by using the method, but the method needs to keep the space-time synchronism of the mask in front of the projector and the camera, and the hardware equipment needs special modulation, so that a measurement system becomes very complicated and is difficult to realize.
The measurement difficulty of high reflection object lies in that what the receiver received is that the surface of high reflection object produces the information after the light aliasing, can't carry out accurate three-dimensional measurement to high reflection object, in order to solve prior art's not enough, needs to study a simple structure, and the precision is higher, has certain commonality, can eliminate the design system that high reflection object surface refraction light aliasing brought the influence.
Disclosure of Invention
In order to overcome the defects of the prior art, the technical problem to be solved by the invention is to provide a high-reflection object measuring method based on laser speckle limit constraint projection, which can accurately complete the measurement of a high-reflection object only by simple laser emission and image acquisition equipment, has a simple structure, does not need to be coated with an anti-reflection material or adopt contact measurement, ensures that the measured object is not damaged, has certain universality for the measurement of common objects in industrial life, effectively reduces the influence caused by the reflected light of the high-reflection object, and improves the three-dimensional measurement precision of the reflection object.
The technical scheme of the invention is as follows: the high-reflection object measuring method based on laser speckle limit constraint projection comprises the following steps:
(1) based on a camera pinhole imaging principle, a camera mathematical model is constructed, and internal parameters and external parameters of the camera are obtained through calculation by using mathematical software;
(2) projecting strip-shaped speckles to the surface of a high-reflection object in the baseline direction of a camera, driving the high-reflection object to move by a translation table, and acquiring a plurality of groups of pictures by the camera;
(3) calibrating the camera parameters obtained in the step (1), and correcting the picture acquired in the step (2) by adopting a Fusiello limit correction method;
(4) performing stereo matching on the group of pictures subjected to limit correction in the step (2) by using compiling software and an image processing library, and solving the parallax of the left and right pictures by using a gray area correlation algorithm to obtain a parallax image;
(5) acquiring three-dimensional point cloud data of a group of pictures according to the disparity map, the camera calibration parameters and the limit correction parameters;
(6) and (5) splicing the point cloud data of the plurality of pictures acquired in the step (5) to reconstruct the three-dimensional shape of the high-reflection object.
The invention marks the parameters of the camera by constructing a camera mathematical model, ensures that a projection system projects strip-shaped speckles in the direction of a camera base line, a displacement table drives a measured object to do linear movement along the vertical direction of the camera base line, a plurality of groups of object pictures with the speckles are shot by the camera, each group of pictures are subjected to limit correction by utilizing a camera calibration result and an ideal imaging model, the aberration of the corrected left and right images is solved by utilizing a gray area correlation method to obtain an aberration diagram, point cloud information at the image strip position is obtained according to the parameters and the aberration diagram after the camera calibration and three-dimensional reconstruction is carried out, therefore, the measurement of a high-reflection object can be accurately finished only by simple laser emission and image acquisition equipment, the structure is simple, anti-reflection materials are not required to be coated or contact measurement is adopted, the measured object is not damaged, and the measurement of common objects, the method has certain universality, effectively reduces the influence caused by the light reflected by the high-reflection object, and improves the three-dimensional measurement precision of the reflection object.
There is also provided a high reflection object measurement system based on laser speckle limit constrained projection, comprising: the device comprises a first optical lens (1), a first CMOS camera (2), a line laser (3), a second CMOS camera (4), a second optical lens (5), a scattering medium (6), a high-reflection object (7) and a translation table (8);
the first CMOS camera (2) and the second CMOS camera (4) are oppositely arranged on the left side and the right side of the translation table, the line laser projects stripe-shaped speckles to the high-reflection object in the baseline direction of the two cameras through the scattering medium, the translation table drives the high-reflection object to do linear motion in the vertical direction of the speckle stripes, and the two CMOS cameras collect multiple groups of pictures.
Drawings
FIG. 1 is a flow chart of a method of high reflectance object measurement based on laser speckle limit constrained projection in accordance with the present invention.
Fig. 2 is a schematic structural diagram of a high-reflection object measurement system based on laser speckle limit constrained projection according to the present invention.
Fig. 3 is a schematic diagram of camera aperture imaging.
Detailed Description
As shown in fig. 1, the method for measuring a highly reflective object based on laser speckle limit constrained projection comprises the following steps:
(1) based on a camera pinhole imaging principle, a camera mathematical model is constructed, and internal parameters and external parameters of the camera are obtained through calculation by using mathematical software;
(2) projecting strip-shaped speckles to the surface of a high-reflection object in the baseline direction of a camera, driving the high-reflection object to move by a translation table, and acquiring a plurality of groups of pictures by the camera;
(3) calibrating the camera parameters obtained in the step (1), and correcting the picture acquired in the step (2) by adopting a Fusiello limit correction method;
(4) performing stereo matching on the group of pictures subjected to limit correction in the step (2) by using compiling software and an image processing library, and solving the parallax of the left and right pictures by using a gray area correlation algorithm to obtain a parallax image;
(5) acquiring three-dimensional point cloud data of a group of pictures according to the disparity map, the camera calibration parameters and the limit correction parameters;
(6) and (5) splicing the point cloud data of the plurality of pictures acquired in the step (5) to reconstruct the three-dimensional shape of the high-reflection object.
The invention marks the parameters of the camera by constructing a camera mathematical model, ensures that a projection system projects strip-shaped speckles in the direction of a camera base line, a displacement table drives a measured object to do linear movement along the vertical direction of the camera base line, a plurality of groups of object pictures with the speckles are shot by the camera, each group of pictures are subjected to limit correction by utilizing a camera calibration result and an ideal imaging model, the aberration of the corrected left and right images is solved by utilizing a gray area correlation method to obtain an aberration diagram, point cloud information at the image strip position is obtained according to the parameters and the aberration diagram after the camera calibration and three-dimensional reconstruction is carried out, therefore, the measurement of a high-reflection object can be accurately finished only by simple laser emission and image acquisition equipment, the structure is simple, anti-reflection materials are not required to be coated or contact measurement is adopted, the measured object is not damaged, and the measurement of common objects, the method has certain universality, effectively reduces the influence caused by the light reflected by the high-reflection object, and improves the three-dimensional measurement precision of the reflection object.
The principle of camera pinhole imaging is shown in fig. 3, where R is the camera coordinate system, S is the image plane coordinate system, and T is the world coordinate system. Preferably, in the step (1),
m (u, v) is a point in the image plane coordinate system, M (X, Y, Z) is a point in the world coordinate system, wherein M and M have a conversion relation of formula (1):
where A represents camera intrinsic parameters, [ R T ] represents camera extrinsic parameters, s is a scale factor from the world coordinate system to the image coordinate system;
the camera parameters are represented using a homography matrix H:
H＝A[R T] (2)
equation (1) is written as equation (3):
preferably, in the step (2), the line laser projects stripe-shaped speckles to the highly reflective object in a baseline direction of the two-phase machine through the scattering medium, the translation stage drives the object to make linear motion along a vertical direction of a speckle stripe, and the left and right CMOS cameras acquire a plurality of groups of pictures.
Preferably, in the step (3), the epipolar line rectification transformation process is regarded as a process that the original optical center position of the camera is unchanged, and an ideal imaging relation is obtained through rotation and projection transformation, and the single mapping matrix of the two imaging systems before transformation is Ho1，Ho2The single mapping matrix of the two imaging systems after conversion is Hn1，Hn2(ii) a The step (3) comprises the following sub-steps:
(3.1) obtaining a single-mapping matrix Ho of the two imaging systems before transformation1，Ho2；
(3.2) obtaining a projection matrix after transformation according to the properties of the single mapping matrixes of the two imaging systems after transformation: hn1，Hn2；
(3.3) obtaining coordinate point m of image before left camera correction according to formula (1)o1And corrected image coordinate points mo2The conversion relation with the point M in the world coordinates is formula (4):
then
(3.4) the transformation matrix before and after limit correction of the image coordinate system is formula (7):
Q1＝Ho1Hn1 -1 (7)
similarly, obtaining a conversion matrix Q before and after limit correction of the image coordinate system of the right camera2＝Ho2Hn2 -1；
(3.5) multiplying all pixel values on the left and right images by the corresponding conversion matrix Q1,Q2And obtaining an imaging image under an ideal condition.
Preferably, in the step (4), in the compiling software, a group of pictures obtained in the step (3) is processed, firstly, a pixel window with the size of (2n +1) × (2m +1) is selected on the left image by taking (i, j) as a coordinate center, then, windows with the same size are searched in the right image along the polar line direction to calculate the correlation coefficient of the left image, the window with the maximum correlation coefficient is calculated to be a matching window of the left image window, and finally, the horizontal axis values of the two matching windows which are matched are subtracted and stored in (i, j) of the disparity map, and the disparity map of the image strip region is obtained through cyclic calculation;
the correlation coefficient is calculated by equation (8):
wherein, C (m)1,m2) Representing the correlation coefficient of two windows, I1(i, j) represents a gray value of the (i, j) coordinate point,
representing the mean value of the gray levels of this window.
Preferably, in the step (5), according to the binocular system after limit correction, the relation between the parallax d and the depth information Z of the world coordinate point is formula (9):
thereby acquiring the three-dimensional information corresponding to the disparity map.
As shown in fig. 2, there is also provided a high reflection object measurement system based on laser speckle limit constrained projection, comprising: the system comprises a first optical lens 1, a first CMOS camera 2, a line laser 3, a second CMOS camera 4, a second optical lens 5, a scattering medium 6, a high-reflection object 7 and a translation table 8;
the first CMOS camera 2 and the second CMOS camera 4 are oppositely arranged on the left side and the right side of the translation table, the line laser projects stripe-shaped speckles to the high-reflection object in the baseline direction of the two-phase machine through the scattering medium, the translation table drives the high-reflection object to do linear motion in the vertical direction of the speckle stripes, and the two CMOS cameras collect multiple groups of pictures.
One embodiment of the present invention is described in detail below. The specific parameters of the projection system and the camera measured in this embodiment are as follows:
type of line laser: 3D PRO Laser, wavelength 635nm, power 5W, working distance 300mm, divergence angle 30 degrees, single line. The camera model: CM3-U3-50S5C-CS, frame rate 35fps, pixel size 4.8um, resolution 2448 x 2048, sensing device CMOS, chip specification 2/3' color camera.
As shown in fig. 1, the method for measuring a high-reflection object based on laser speckle limit constrained projection disclosed in this embodiment includes the following specific steps:
step 1: based on the camera pinhole imaging principle, a camera mathematical model is constructed, and internal parameters and external parameters of the camera are obtained through calculation by using mathematical software.
Specifically, a checkerboard calibration plate of 10 rows and 10 columns, each having a size of 10mm × 10mm, was photographed using a CMOS camera, and the inclination angle and position of the checkerboard were freely adjusted, and a total of 10 pictures were photographed. In this embodiment, MATLAB is selected as mathematical software to extract corner points of a checkerboard picture, coordinates of the checkerboard in a world coordinate system are known, a homography matrix H is solved according to formula (1), and an internal parameter a and an external parameter are calculated by using an analytic estimation method [ R T ].
Step 2: strip-shaped speckles are projected to the surface of the high-reflection object in the baseline direction of the camera, the translation table drives the high-reflection object to move, and the camera collects multiple groups of pictures.
Specifically, the line laser projects stripe-shaped speckles to a high-reflection object in the baseline direction of the two cameras through a scattering medium (ground glass), the translation stage drives the object to continuously move along the vertical direction of a speckle stripe, and the left CMOS camera and the right CMOS camera acquire multiple groups of pictures.
And step 3: and (3) calibrating the obtained camera parameters in the step (1), and correcting the picture acquired in the step (2) by adopting a Fusiello limit correction method.
(1) From step 1, a single mapping matrix Ho of the two imaging systems before transformation is obtained1，Ho2。
(2) And obtaining a projection matrix after transformation according to the properties of the single mapping matrixes of the two imaging systems after transformation: hn1，Hn2。
(3) Obtaining a conversion matrix Q before and after limit correction of the image coordinate system by the formula (7)1，Q2。
(4) Multiplying all pixel values on the left and right images by the corresponding conversion matrix Q1，Q2And obtaining an imaging picture under the ideal condition of the imaging system.
And 4, step 4: and (3) performing stereo matching on a group of pictures acquired by the left camera and the right camera in the step (2) by using compiling software and an image processing library, and solving the parallax of the left picture and the right picture by using a gray area correlation algorithm to obtain a parallax image.
And selecting Visual Studio and OpenCV as compiling software and an image processing library to process the picture. Selecting a pixel window with the size of (2n +1) × (2m +1) on the left image by taking (i, j) as a coordinate origin, searching the window with the same size along the polar line direction on the right image, calculating the correlation coefficient C by using a formula (8), and considering the window with the large correlation coefficient as a best matching window. The coordinate values of the horizontal axes of the two matching windows are subtracted from each other and stored in (i, j) of the disparity map. And (3) selecting a pixel window with the size of (2n +1) × (2m +1) on the left image by taking (i +1, j) as a coordinate center, and sequentially calculating according to the method to obtain the whole disparity map.
And 5: and acquiring three-dimensional point cloud data of a group of pictures according to the parallax map in the step 4, the camera calibration parameters in the step 1 and the limit correction parameters in the step 3.
Obtaining the depth information Z value of the world coordinate point M according to the formula (9):
the disparity map is converted into world coordinate points M (X, Y, Z) according to the limit correction parameters. And converting the parallax of the pixels in the strip area on the parallax picture into a three-dimensional space coordinate point cloud of the area.
Step 6: and (5) splicing the point cloud data of the plurality of pictures acquired in the step (5) to reconstruct the three-dimensional appearance of the high-reflection object.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications, equivalent variations and modifications made to the above embodiment according to the technical spirit of the present invention still belong to the protection scope of the technical solution of the present invention.
Claims (7)
1. The high-reflection object measuring method based on laser speckle limit constraint projection is characterized in that: which comprises the following steps:
(1) based on a camera pinhole imaging principle, a camera mathematical model is constructed, and internal parameters and external parameters of the camera are obtained through calculation by using mathematical software;
(2) projecting strip-shaped speckles to the surface of a high-reflection object in the baseline direction of a camera, driving the high-reflection object to move by a translation table, and acquiring a plurality of groups of pictures by the camera;
(3) calibrating the camera parameters obtained in the step (1), and correcting the picture acquired in the step (2) by adopting a Fusiello limit correction method;
(4) performing stereo matching on the group of pictures subjected to limit correction in the step (2) by using compiling software and an image processing library, and solving the parallax of the left and right pictures by using a gray area correlation algorithm to obtain a parallax image;
(5) acquiring three-dimensional point cloud data of a group of pictures according to the disparity map, the camera calibration parameters and the limit correction parameters;
(6) and (5) splicing the point cloud data of the plurality of pictures acquired in the step (5) to reconstruct the three-dimensional shape of the high-reflection object.
2. The method for measuring the high-reflection object based on the laser speckle limit constraint projection, according to claim 1, is characterized in that: in the step (1), the step (c),
m (u, v) is a point in the image plane coordinate system, M (X, Y, Z) is a point in the world coordinate system, wherein M and M have a conversion relation of formula (1):
where A represents camera intrinsic parameters, [ R T ] represents camera extrinsic parameters, s is a scale factor from the world coordinate system to the image coordinate system;
the camera parameters are represented using a homography matrix H:
H＝A[R T] (2)
equation (1) is written as equation (3):
3. the method for measuring the high-reflection object based on the laser speckle limit constraint projection according to claim 2, is characterized in that: in the step (2), the line laser projects stripe-shaped speckles to the high-reflection object in the baseline direction of the two-phase machine through the scattering medium, the translation table drives the object to do linear motion along the vertical direction of the speckle stripes, and the left CMOS camera and the right CMOS camera acquire a plurality of groups of pictures.
4. The method of claim 3, wherein the method comprises measuring the height of the object based on the laser speckle limit constrained projection: in the step (3), the polar line correction transformation process is regarded as a process that the original optical center position of the camera is unchanged, an ideal imaging relation is obtained through rotation and projection transformation, and the single mapping matrixes of the two imaging systems before transformation are Ho1，Ho2The single mapping matrix of the two imaging systems after conversion is Hn1，Hn2(ii) a The step (3) comprises the following sub-steps:
(3.1) obtaining a single-mapping matrix Ho of the two imaging systems before transformation1，Ho2；
(3.2) obtaining a projection matrix after transformation according to the properties of the single mapping matrixes of the two imaging systems after transformation: hn1，Hn2；
(3.3) obtaining coordinate point m of image before left camera correction according to formula (1)o1And corrected image coordinate points mn1The conversion relation with the point M in the world coordinates is formula (4):
then
(3.4) the transformation matrix before and after limit correction of the image coordinate system is formula (7):
Q1＝Ho1Hn1 -1 (7)
similarly, obtaining a conversion matrix Q before and after limit correction of the image coordinate system of the right camera2＝Ho2Hn2 -1；
(3.5) multiplying all pixel values on the left and right images by the corresponding conversion matrix Q1,Q2And obtaining an imaging image under an ideal condition.
5. The method of claim 4, wherein the method comprises: in the step (4), in the compiling software, processing the group of pictures obtained in the step (3), firstly, selecting a pixel window with the size of (2n +1) × (2m +1) on the left image by taking (i, j) as a coordinate center, then searching windows with the same size in the direction of polar lines on the right image to calculate the correlation coefficient of the left image, calculating to obtain a window with the maximum correlation coefficient, namely a matching window of the left image window, finally subtracting the horizontal axis values of the two matched windows, storing the horizontal axis values in the (i, j) of the disparity map, and circularly calculating to obtain the disparity map of the image strip area;
the correlation coefficient is calculated by equation (8):
wherein, C (m)1,m2) Representing the correlation coefficient of two windows, I1(i, j) represents a gray value of the (i, j) coordinate point,
representing the mean value of the gray levels of this window.
6. The method of claim 5, wherein the method comprises: in the step (5), according to the binocular system after limit correction, a relational expression between the parallax d and the depth information Z of the world coordinate point is formula (9):
thereby acquiring the three-dimensional information corresponding to the disparity map.
7. The system of claim 1, wherein the system comprises: it includes: the device comprises a first optical lens (1), a first CMOS camera (2), a line laser (3), a second CMOS camera (4), a second optical lens (5), a scattering medium (6), a high-reflection object (7) and a translation table (8);
the first CMOS camera (2) and the second CMOS camera (4) are oppositely arranged on the left side and the right side of the translation table, the line laser projects stripe-shaped speckles to the high-reflection object in the baseline direction of the two cameras through the scattering medium, the translation table drives the high-reflection object to do linear motion in the vertical direction of the speckle stripes, and the two CMOS cameras collect multiple groups of pictures.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101908230A (en) * | 2010-07-23 | 2010-12-08 | 东南大学 | Regional depth edge detection and binocular stereo matching-based three-dimensional reconstruction method |
| CN101915559A (en) * | 2010-08-02 | 2010-12-15 | 山东师范大学 | Method and system thereof for measuring three-dimensional surface shape of object by electronic speckle phase shift technology |
| CN103868472A (en) * | 2013-12-23 | 2014-06-18 | 黑龙江科技大学 | Planar structured light three dimension measuring device and method for high-reflectivity part |
| CN104634276A (en) * | 2015-02-12 | 2015-05-20 | 北京唯创视界科技有限公司 | Three-dimensional measuring system, photographing device, photographing method, depth calculation method and depth calculation device |
| CN105928472A (en) * | 2016-07-11 | 2016-09-07 | 西安交通大学 | Three-dimensional shape dynamic measurement method based on active spot projector |
| CN106091987A (en) * | 2016-06-14 | 2016-11-09 | 中国科学院上海光学精密机械研究所 | Based on the large scale optical blank method for three-dimensional measurement that speckle time domain is relevant |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20080043047A (en) * | 2006-11-13 | 2008-05-16 | 주식회사 고영테크놀러지 | Three-dimensional image measuring apparatus using shadow moire |
-
2019
- 2019-11-29 CN CN201911202640.XA patent/CN110940295B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101908230A (en) * | 2010-07-23 | 2010-12-08 | 东南大学 | Regional depth edge detection and binocular stereo matching-based three-dimensional reconstruction method |
| CN101915559A (en) * | 2010-08-02 | 2010-12-15 | 山东师范大学 | Method and system thereof for measuring three-dimensional surface shape of object by electronic speckle phase shift technology |
| CN103868472A (en) * | 2013-12-23 | 2014-06-18 | 黑龙江科技大学 | Planar structured light three dimension measuring device and method for high-reflectivity part |
| CN104634276A (en) * | 2015-02-12 | 2015-05-20 | 北京唯创视界科技有限公司 | Three-dimensional measuring system, photographing device, photographing method, depth calculation method and depth calculation device |
| CN106091987A (en) * | 2016-06-14 | 2016-11-09 | 中国科学院上海光学精密机械研究所 | Based on the large scale optical blank method for three-dimensional measurement that speckle time domain is relevant |
| CN105928472A (en) * | 2016-07-11 | 2016-09-07 | 西安交通大学 | Three-dimensional shape dynamic measurement method based on active spot projector |
Non-Patent Citations (1)
| Title |
|---|
| A compact algorithm for rectification of stereo pairs;Fusiello, A. et al.;《Machine Vision and Applications》;20001231(第12期);第12-16页 * |
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