The Study Of Stereo Matching Algorithm Based On Multi-Baseline Trinocular Model

Stereo vision is one of the widely studied subjects in computer vision areas,and it plays an important role in many applications,such as robot obstacle avoidance,3D reconstruction and automatic driving.As the core problem of stereo vision,stereo matching algorithm to a large extent determines the accuracy and time consumption of the whole system,while the huge computational complexity,occlusion,weak texture,light and shadow problems make stereo matching a great challenge.The traditional binocular stereo matching algorithm is difficult to overcome these problems.In this paper,we optimize the stereo matching algorithm based on the multi-baseline trinocular camera model to solve the above problems,and build a trinocular stereo vision system to implement the algorithm.The specific results are as follows:(1)Based on the horizontal multi-baseline trinocular camera model,an optimization scheme named trinocular dynamic disparity range is proposed to speed up the stereo matching algorithm,In this scheme,the disparity map generated by the narrow-baseline camera is taken as the prior knowledge,and the reduced dynamic disparity search range is calculated for each pixel of the image of the wide-baseline camera,which will be used for wide-baseline stereo matching and can greatly reduce the computational complexity of the algorithm when the ground truth is included.The improved algorithm based on this scheme can greatly reduce the time consumption and significantly improve the algorithm efficiency while the accuracy of the disparity estimation is basically unchanged.(2)In order to improve the accuracy of disparity estimation and deal with the problem of mismatching caused by occlusion,weak texture and light and shadow regions,we proposed an optimization scheme named trinocular disparity confidence measure based on the non-collinear multi-baseline trinocular camera model.The purpose of the scheme is to establish a set of measurement methods to evaluate the reliability of the disparity value.By virtue of the characteristics of the horizontal and vertical binocular cameras of the trinocular camera model,the disparity map generated by the model can be complementary to each other and the accuracy of the disparity estimation can be significantly improved.The optimized algorithm based on this scheme can greatly improve the mismatching of occlusion,weak texture,light and shadow problems,and at the same time,the calculation speed can be ensured by parallel computation.(3)We complete the construction process of the trinocular stereo vision system,research and design the system scheme,explore the principle of the trinocular camera calibration and complete the stereo calibration of the system.