CN112697065A - Three-dimensional shape reconstruction method based on camera array - Google Patents

Three-dimensional shape reconstruction method based on camera array Download PDF

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CN112697065A
CN112697065A CN202011323433.2A CN202011323433A CN112697065A CN 112697065 A CN112697065 A CN 112697065A CN 202011323433 A CN202011323433 A CN 202011323433A CN 112697065 A CN112697065 A CN 112697065A
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CN112697065B (en
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费庆国
胡甜赐
朱锐
姜东�
马蕾
曹芝腑
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Southeast University
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    • 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

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Abstract

A three-dimensional shape reconstruction method based on a camera array relates to the field of non-contact optical measurement. The method specifically comprises the following steps: building a camera array system; fixing a tested piece, spraying random speckles on the surface of the tested piece, dividing the tested piece into two measuring areas, wherein the two measuring areas have an overlapping area, and controlling a camera to take a picture; solving world coordinates of the calculation points in the overlapping area under two world systems by adopting a multi-time speckle matching method; and unifying the world coordinates of all the measuring points to a coordinate system, and reconstructing the three-dimensional appearance of the measured object. The invention is based on the sub-pixel speckle matching method, four cameras are adopted to form a camera array, no additional operation is needed, and the reconstruction of the three-dimensional appearance of the large-size object can be realized through calculation according to the overlapping area between the pictures shot by the cameras.

Description

Three-dimensional shape reconstruction method based on camera array
Technical Field
The invention relates to the field of non-contact optical measurement, in particular to a three-dimensional shape reconstruction method based on a camera array.
Background
In the fields of aerospace and the like, great demands are made on accurate measurement of the three-dimensional shape of an object. For some objects with higher precision and greater flexibility, the traditional contact measurement method cannot be used for measurement sometimes. In recent years, optical measurement has been greatly developed with the development of optical instruments and equipment and with the reduction of cost. Digital image correlation is a non-contact measurement method based on optical measurement, and is widely applied to displacement, strain and other measurements. The traditional three-dimensional digital image related measurement system formed by two cameras has a limited measurement range, and cannot realize measurement of large-size test pieces. Therefore, how to reconstruct the three-dimensional shape of a large-size object by using a camera array composed of a plurality of cameras is an actual engineering problem which needs to be solved urgently.
Disclosure of Invention
The invention provides a three-dimensional shape reconstruction method based on a camera array, and aims to realize the reconstruction of the three-dimensional shape of a large-size object by calculation according to an overlapped region of pictures shot by a camera based on a sub-pixel point speckle matching method.
In order to achieve the technical purpose, the invention adopts the following technical scheme:
a three-dimensional shape reconstruction method based on a camera array comprises the following steps:
(1) building a camera array system, wherein the camera array system comprises four cameras C1, C2, C3 and C4, the cameras C1 and C2 form a set of three-dimensional digital image related measurement system, and the cameras C3 and C4 form a set of three-dimensional digital image related measurement system;
(2) fixing a tested piece, spraying random speckles on the surface of the tested piece, dividing the tested piece into two measurement areas A1 and A2, wherein an overlapping area exists between A1 and A2, controlling cameras to shoot, shooting an A1 area by the cameras C1 and C2, shooting an A2 area by the cameras C3 and C4, and shooting pictures by the four cameras are Img1, Img2, Img3 and Img4 respectively;
(3) calculating world coordinates of two shooting areas of the tested piece by adopting a three-dimensional digital image correlation algorithm;
(4) adopting a multi-time speckle matching method to obtain world coordinates of a calculation point in the camera overlapping area under two world systems;
(5) and calculating the world coordinates of the points according to the overlapped area, solving a rotation matrix R and a translation matrix T converted between two world coordinate systems, unifying the world coordinates of all the measuring points to a coordinate system, and reconstructing the three-dimensional shape of the measured object.
Preferably, in the step (3), the step of calculating the world coordinates of the calculation points of the two shooting areas of the tested piece by using a three-dimensional digital image correlation algorithm is as follows:
(31) calculating the world coordinates of scattered spots in the shooting area of the cameras C1 and C2 by taking Img1 and Img2 as calculation images and adopting a three-dimensional digital image correlation algorithm, wherein the world coordinates are the optical center coordinate system of the camera C2;
(32) and calculating the world coordinates of scattered spots in the shooting area of the cameras C3 and C4 by taking Img3 and Img4 as calculation images and adopting a three-dimensional digital image correlation algorithm, wherein the world coordinates are the optical center coordinate system of the camera C3.
Preferably, in the step (4), the step of calculating the world coordinates of the calculation point in the overlapped area of the tested piece in the two world coordinate systems by using a multiple speckle matching method is as follows:
(41) selecting scattered spots (x) to be calculated in image coordinates from the overlapped area in Img221,y21) Selecting a square subregion as a template by taking the speckle point as a central point, and calculating the world coordinate (x) of the speckle point in a world coordinate system by using the optical center coordinate system of the camera C2 through a three-dimensional digital image correlation algorithmw21,yw21,zw21)；
(42) Searching for scattered spots (x) in Img3 by first speckle matching21,y21) Corresponding image coordinates (x)31,y31)；
(43) Searching for scattered spots (x) in Img4 by second speckle matching21,y21) Corresponding image coordinates (x)41,y41)；
(44) According to the binocular vision principle, the world coordinate of the speckle point in the world coordinate system based on the optical center coordinate system of the camera C3 is calculatedLabel (x)w31,yw31,zw31)；
(45) And (5) repeating the steps (41), (42), (43) and (44), and calculating the world coordinates of the N speckle points of the coincident region in two world coordinate systems respectively, wherein N > 4.
Further preferably, in the step (5), the world coordinates of the points are calculated according to the overlapping region, a rotation matrix R and a translation matrix T converted between two world coordinate systems are obtained, and the world coordinates of all the measurement points are unified under one coordinate system, so as to reconstruct the three-dimensional shape of the measured object, which specifically includes the following steps:
transforming the relationship according to a coordinate system:
Figure BDA0002793610570000021
wherein R is a rotation matrix, T is a translation matrix, and i represents scattered spots;
calculating N equations from the N calculation points, and subtracting the speckle point of the equation obtained from the first calculation point to obtain:
Figure BDA0002793610570000022
writing in matrix form:
Figure BDA0002793610570000023
namely:
Xw2＝RXw3
wherein:
Figure BDA0002793610570000031
Figure BDA0002793610570000032
the rotation matrix R is calculated by the least square method:
Figure BDA0002793610570000033
obtaining a translation matrix T:
Figure BDA0002793610570000034
and transforming the coordinates of all the measuring points shot by the cameras C3 and C4 into a world coordinate system by using the optical center coordinate system of the C2 camera according to the obtained rotation matrix and translation matrix, and reconstructing the complete three-dimensional shape of the tested piece.
Advantageous effects
The invention is based on the sub-pixel speckle matching method, four cameras are adopted to form a camera array, no additional operation is needed, and the reconstruction of the three-dimensional appearance of the large-size object can be realized through calculation according to the overlapping area between the pictures shot by the cameras.
Drawings
FIG. 1 is a schematic diagram illustrating the division of a measurement area of a test object;
FIG. 2 is a computational flow diagram of the present invention;
FIG. 3 is a schematic diagram of sub-pixel template selection;
FIG. 4 is a speckle image of a tested object collected by four cameras;
FIG. 5 is a three-dimensional topographic map of the measuring area of the cameras C1 and C2 with the optical center coordinate system of C2 as the world coordinate system;
FIG. 6 is a three-dimensional topographic map of the measuring area of the cameras C3 and C3 with the optical center coordinate system of C3 as the world coordinate system;
FIG. 7 is a complete topography of the tested piece after coordinate system transformation.
Detailed Description
The present invention will be described in detail with reference to the accompanying drawings.
Random speckles are sprayed on the surface of a tested piece, a camera array consisting of four cameras is built, every two cameras are responsible for measuring a part of area of the tested piece, a sub-pixel point speckle matching method is adopted for speckle matching, a conversion matrix among different world coordinate systems is obtained, and finally all measuring points are unified under one world coordinate system to reconstruct the three-dimensional appearance of the surface of an object. The method comprises the following specific steps:
step 1, a camera array system is built, as shown in fig. 1, the camera array system comprises four cameras C1, C2, C3 and C4, wherein the cameras C1 and C2 form a set of three-dimensional digital image related measurement system, and the cameras C3 and C4 form a set of three-dimensional digital image related measurement system.
Step 2, fixing the tested piece, spraying random speckles on the surface of the tested piece, dividing the tested piece into two measurement areas A1 and A2, wherein an overlapping area exists between A1 and A2, controlling cameras to shoot, cameras C1 and C2 shoot an area A1, cameras C3 and C4 shoot an area A2, and four cameras respectively shoot an area Img1, an area Img2, an area g3 and an area g4, as shown in FIG. 4.
Step 3, calculating world coordinates of two shooting areas of the tested piece by adopting a three-dimensional digital image correlation algorithm;
(31) taking Img1 and Img2 as calculation images, calculating the world coordinates of scattered spots in shooting areas of cameras C1 and C2 by adopting a three-dimensional digital image correlation algorithm, wherein the world coordinates are the optical center coordinates of the camera C2, as shown in FIG. 5;
(32) the world coordinates of scattered spots in the shooting area of the cameras C3 and C4 are calculated by taking Img3 and Img4 as calculation images and adopting a three-dimensional digital image correlation algorithm, and the world coordinates are the optical center coordinates of the camera C3, as shown in FIG. 6.
Step 4, solving world coordinates of the calculation points in the camera overlapping area under two world systems by adopting a multi-time speckle matching method, as shown in fig. 2;
(41) selecting scattered spots (x) to be calculated in image coordinates from the overlapped area in Img221,y21) Selecting a square subregion as a template by taking the speckle point as a central point, and calculating the world coordinate (x) of the speckle point in a world coordinate system by using the optical center coordinate system of the camera C2 through a three-dimensional digital image correlation algorithm as shown in FIG. 3w21,yw21,zw21)；
(42) Searching for scattered spots (x) in Img3 by first speckle matching21,y21) Corresponding image coordinates (x)31,y31)；
(43) Searching for scattered spots (x) in Img4 by second speckle matching21,y21) Corresponding image coordinates (x)41,y41)；
(44) According to the binocular vision principle, the world coordinate (x) of the speckle point in the world coordinate system is calculated by using the optical center coordinate system of the camera C3w31,yw31,zw31)；
(45) And (5) repeating the steps (41), (42), (43) and (44), and calculating the world coordinates of the N speckle points of the coincident region in two world coordinate systems respectively, wherein N > 4.
And 5, calculating the world coordinates of the points according to the overlapped area, solving a rotation matrix R and a translation matrix T converted between two world coordinate systems, unifying the world coordinates of all the measuring points to a coordinate system, and reconstructing the three-dimensional appearance of the measured object. Transforming the relationship according to a coordinate system:
Figure BDA0002793610570000051
wherein R is a rotation matrix, T is a translation matrix, and i represents scattered spots;
calculating N equations from the N calculation points, and subtracting the speckle point of the equation obtained from the first calculation point to obtain:
Figure BDA0002793610570000052
writing in matrix form:
Figure BDA0002793610570000053
namely:
Xw2＝RXw3
wherein:
Figure BDA0002793610570000054
Figure BDA0002793610570000055
the rotation matrix R is calculated by the least square method:
Figure BDA0002793610570000056
obtaining a translation matrix T:
Figure BDA0002793610570000057
and transforming the coordinates of all the measuring points shot by the cameras C3 and C4 into a world coordinate system by using the optical center coordinate system of the C2 camera according to the obtained rotation matrix and translation matrix, and reconstructing the complete three-dimensional topography of the tested piece, as shown in FIG. 7.

Claims (4)

1. A three-dimensional shape reconstruction method based on a camera array is characterized by comprising the following steps:
(1) building a camera array system, wherein the camera array system comprises four cameras C1, C2, C3 and C4, the cameras C1 and C2 form a set of three-dimensional digital image related measurement system, and the cameras C3 and C4 form a set of three-dimensional digital image related measurement system;
(2) fixing a tested piece, spraying random speckles on the surface of the tested piece, dividing the tested piece into two measurement areas A1 and A2, wherein an overlapping area exists between A1 and A2, controlling cameras to shoot, shooting an A1 area by the cameras C1 and C2, shooting an A2 area by the cameras C3 and C4, and shooting pictures by the four cameras are Img1, Img2, Img3 and Img4 respectively;
(3) calculating world coordinates of two shooting areas of the tested piece by adopting a three-dimensional digital image correlation algorithm;
(4) adopting a multi-time speckle matching method to obtain world coordinates of a calculation point in the camera overlapping area under two world systems;
(5) and calculating the world coordinates of the points according to the overlapped area, solving a rotation matrix R and a translation matrix T converted between two world coordinate systems, unifying the world coordinates of all the measuring points to a coordinate system, and reconstructing the three-dimensional shape of the measured object.
2. The method for reconstructing the three-dimensional topography based on the camera array as claimed in claim 1, wherein in the step (3), the step of calculating the world coordinates of the calculation points of the two parts of the shooting area of the tested piece by using the three-dimensional digital image correlation algorithm comprises the following steps:
(31) calculating the world coordinates of scattered spots in the shooting area of the cameras C1 and C2 by taking Img1 and Img2 as calculation images and adopting a three-dimensional digital image correlation algorithm, wherein the world coordinates are the optical center coordinate system of the camera C2;
(32) and calculating the world coordinates of scattered spots in the shooting area of the cameras C3 and C4 by taking Img3 and Img4 as calculation images and adopting a three-dimensional digital image correlation algorithm, wherein the world coordinates are the optical center coordinate system of the camera C3.
3. The method for reconstructing three-dimensional topography based on camera array according to claim 1, wherein the step (4) of using a multiple speckle matching method to find the world coordinates of the calculated points in the overlapped area of the tested piece in two world coordinate systems comprises the following steps:
(41) selecting scattered spots (x) to be calculated in image coordinates from the overlapped area in Img221,y21) Selecting a square subregion as a template by taking the speckle point as a central point, and calculating the world coordinate (x) of the speckle point in a world coordinate system by using the optical center coordinate system of the camera C2 through a three-dimensional digital image correlation algorithmw21,yw21,zw21)；
(42) Searching for scattered spots (x) in Img3 by first speckle matching21,y21) Corresponding image coordinates (x)31,y31)；
(43) Searching for scattered spots (x) in Img4 by second speckle matching21,y21) Corresponding image coordinates (x)41,y41)；
(44) According to the binocular vision principle, the world coordinate (x) of the speckle point in the world coordinate system is calculated by using the optical center coordinate system of the camera C3w31,yw31,zw31)；
(45) And (5) repeating the steps (41), (42), (43) and (44), and calculating the world coordinates of the N speckle points of the coincident region in two world coordinate systems respectively, wherein N > 4.
4. The method for reconstructing the three-dimensional topography based on the camera array as claimed in claim 3, wherein in the step (5), the world coordinates of the points are calculated according to the overlapping region, the rotation matrix R and the translation matrix T converted between the two world coordinate systems are obtained, and the world coordinates of all the measurement points are unified under one coordinate system, so as to reconstruct the three-dimensional topography of the measured object, which comprises the following steps: transforming the relationship according to a coordinate system:
Figure FDA0002793610560000021
wherein R is a rotation matrix, T is a translation matrix, and i represents scattered spots;
calculating N equations from the N calculation points, and subtracting the speckle point of the equation obtained from the first calculation point to obtain:
Figure FDA0002793610560000022
writing in matrix form:
Figure FDA0002793610560000023
namely:
Xw2＝RXw3
wherein:
Figure FDA0002793610560000024
Figure FDA0002793610560000025
the rotation matrix R is calculated by the least square method:
Figure FDA0002793610560000026
obtaining a translation matrix T:
Figure FDA0002793610560000027
and transforming the coordinates of all the measuring points shot by the cameras C3 and C4 into a world coordinate system by using the optical center coordinate system of the C2 camera according to the obtained rotation matrix and translation matrix, and reconstructing the complete three-dimensional shape of the tested piece.
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