Parallax-tolerant Image Stitching Based on Mesh Optimization
Image stitching with large parallax has long been an important and challenging issue in computer graph and vision.Most studies focused on finding the best-fitting homography to align and seam the input images.Images with large parallax can not be mapped over the whole overlapping regions or aircrafts like ghosting and distortion may occur.In this paper,We combine the global 2D homography method with local warping based on mesh optimization.Instead of finding the best-fitting mapping relationships among input images,we align them loosely by SIFT feature points,and then refine the local areas with mesh optimization.Four constraints are considered during local warping,including the matching error,regular error,scale error and linearity error.Finally,for the image sequence,a tree-structure stitching method is proposed to reduce the accumulated error during the continuous aligning and seaming.The comparison experiments show that,our parallax-tolerant image stitching based on mesh optimization can handle parallax well.
image stitching large parallax losse global homography mesh optimization
Xin Pan Geng Wang
Shanghai Jiao Tong University Shanghai,China
国际会议
重庆
英文
414-420
2017-03-25（万方平台首次上网日期，不代表论文的发表时间）