The existing panoramic image matching methods are difficult to overcome the non-uniform features of the projection transformation of the target object,and hence the issue of unstable corresponding points matching is u...The existing panoramic image matching methods are difficult to overcome the non-uniform features of the projection transformation of the target object,and hence the issue of unstable corresponding points matching is usually induced.This paper aims to solve the difficulty by proposing a sparse depth point set matching method based on panoramic disparity.By constructing a panoramic disparity model of stereo panoramic images,the disparity between corresponding points can be precisely estimated,and the robustness and effectiveness of corresponding points matching between stereo panoramic images is improved under the epipolar geometric constraints.Firstly,by defining the panoramic disparity,the corresponding angle of panoramic disparity is derived,and the matching areas of corresponding points based on the disparity corresponding angle difference are partitioned.Secondly,the optimization strategy in the matching process of corresponding points is constructed to provide stable matching results for generating sparse depth maps based on the disparity region range and epipolar geometric relationship.Experiments show that the proposed method can not only obtain more stable matching results but also exhibit higher computational efficiency than existing algorithms.展开更多
基金National Natural Science Foundation of China(No.41761079)Top Young Talent Project of Yunnan Province in China.
文摘The existing panoramic image matching methods are difficult to overcome the non-uniform features of the projection transformation of the target object,and hence the issue of unstable corresponding points matching is usually induced.This paper aims to solve the difficulty by proposing a sparse depth point set matching method based on panoramic disparity.By constructing a panoramic disparity model of stereo panoramic images,the disparity between corresponding points can be precisely estimated,and the robustness and effectiveness of corresponding points matching between stereo panoramic images is improved under the epipolar geometric constraints.Firstly,by defining the panoramic disparity,the corresponding angle of panoramic disparity is derived,and the matching areas of corresponding points based on the disparity corresponding angle difference are partitioned.Secondly,the optimization strategy in the matching process of corresponding points is constructed to provide stable matching results for generating sparse depth maps based on the disparity region range and epipolar geometric relationship.Experiments show that the proposed method can not only obtain more stable matching results but also exhibit higher computational efficiency than existing algorithms.
