Rectangling irregular videos by optimal spatio-temporal warping - Jin-Liang Wu; Jun-Jie Shi; Lei Zhang (Computational Visual Media, 2021)
Abstract Image and video processing based on geometric principles typically changes the rectangular shape of video frames to an irregular shape. This paper presents a warping based approach for rectangling such irregular frame boundaries in space and time, i.e., making them rectangular again. To reduce geometric distortion in the rectangling process, we employ content-preserving deformation of a mesh grid with line structures as constraints to warp the frames. To conform to the original inter-frame motion, we keep feature trajectory distribution as constraints during motion compensation to ensure stability after warping the frames. Such spatially and temporally optimized warps enable the output of regular rectangular boundaries for the video frames with low geometric distortion and jitter. Our experiments demonstrate that our approach can generate plausible video rectangling results in a variety of applications.