Belief Propagation Algorithm for Epipolar Matching in Panoramic Longitudinal Roamin

Depth information acquisition is the key foundation of panoramic longitudinal roaming.In order to improve the accuracy of before and after scene images matching,the belief propagation algorithm for the epipolar matching is proposed.According to the principle of epipolar geometry,the epipolar line of scene images is constructed by taking the image center as the benchmark and diverging in the whole direction.The vertical matching cost component is added to the matching cost function,and the disparity map is generated by the belief propagation algorithm.Through the geometric relationship between the scene images,the model of disparity and depth is constructed to obtain the depth information.Experimental results show that,compared with the local optimization algorithms,this algorithm is better for obtaining the depth map of scene images.SSIM and PSNR are improved by 0.22 and 24%respectively.