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Binocular three-dimensional reconstruction method

A 3D reconstruction and dual-purpose technology, applied in 3D modeling, image data processing, instruments, etc., can solve the problems of high algorithm complexity, reduce the error matching rate, improve the matching accuracy rate, and reduce the scope of the effect

Inactive Publication Date: 2013-04-24
SOUTH CHINA UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0003] In the existing binocular 3D reconstruction process, there is a contradiction between the amount of feature information and the matching accuracy in image feature extraction and matching, and the algorithm complexity of image feature extraction and matching is very high

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  • Binocular three-dimensional reconstruction method

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Embodiment

[0023] Such as figure 1 As shown, a method for binocular 3D reconstruction includes the following steps:

[0024] Step A: Image acquisition, such as figure 1 In the image acquisition part of, this method uses two CCD cameras of the same model, fixed on the optical platform, the lens is in the same plane, can move left and right to change the horizontal distance D of the two cameras, D can be directly read from the optical platform, As a parameter calculated below; D has no specified value, and the value of D is based on the principle that the target object can be imaged in the center of the image. Place the three-dimensional object to be reconstructed on the test bench, adjust D to an appropriate position and record its value, fix two cameras for image collection, and the images collected by the left and right cameras are respectively recorded as I1 and I2;

[0025] Step B1: Camera calibration and image correction, such as figure 1 In the camera calibration and correction part of t...

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Abstract

A binocular three-dimensional reconstruction method includes the following steps: step A, image collection: using two color cameras with the same model and arranging the two color cameras horizontally in a parallel mode, and enabling an target object to be arranged within the collecting range of the two cameras, wherein a image collected by a left camera is an original left image and a image collected by a right camera is an original right image; step B, camera calibration, and image rectification and pretreatment: adopting a chessboard method to demarcate and obtain inner and outer diameters of the two cameras, and then rectifying the original left image and the original right image, and next, pretreating the images; step C, hierarchical matching: conducting hierarchical feature extraction and matching to the images according to strong and week of feature lines of the images; step D, three-dimensional reconstruction: after completing the delamination which reaches required precision, according to a parallax principle, enabling obtained matching information of the two images to be calculated into three-dimensional information of the target object, adopting a method of plane interpolation, and then completing the three-dimensional reconstruction. The method has the advantages of being low in algorithm complexity and capable of achieving the three-dimensional reconstruction well and the like.

Description

Technical field [0001] The invention relates to a machine vision and image matching technology, in particular to a binocular three-dimensional reconstruction method. Background technique [0002] Binocular 3D reconstruction is a very important research field in machine vision, which is widely used in medical cosmetic surgery, intelligent recognition, archaeology, and computational 3D animation. Binocular 3D reconstruction includes image acquisition, camera calibration, image correction, image feature extraction and matching, and 3D reconstruction. The image feature extraction and matching are the core part of the entire binocular 3D reconstruction process and the difficulty lies. At present, most image feature extraction and matching algorithms have a contradiction: when the extracted feature amount is enough, the matching error rate of the image will be greatly improved. The most typical example is image edge extraction. The extracted edge points or linearity are enough, but I...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/00G06T7/00
Inventor 徐晓赵林献
Owner SOUTH CHINA UNIV OF TECH
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