Efficient Video Stitching Based on Fast

In computer vision, video stitching is a very chal- lenging problem. In this paper, we proposed an efficient and effective wide-view video stitching method based on fast struc- ture deformation that is capable of simultaneously achieving quality stitching and computational efficiency. For a group of synchronized frames, firstly, an effective double-seam selection scheme is designed to search two distinct but structurally corre- sponding seams in the two original images. The seam location of the previous frame is further considered to preserve the inter- frame consistency. Secondly, along the double seams, 1-D feature detection and matching is performed to capture the structural relationship between the two adjacent views. Thirdly, after fea- ture matching, we propose an efficient algorithm to linearly propagate the deformation vectors to eliminate structure mis- alignment. At last, image intensity misalignment is corrected by rapid gradient fusion based on the successive over relaxation iteration (SORI) solver. A principled solution to the initializa- tion of the SORI significantly reduced the number of iterations required. We have compared favorably our method with seven state-of-the-art image and video stitching algorithms as well as traditional ones. Experimental results show that our method out- performs the existing ones compared in terms of overall stitching quality and computational efficiency.