Efficient video stitching based on fast structure deformation

Jing Li, Wei Xu, Jianguo Zhang, Maojun Zhang, Zhengming Wang, Xuelong Li

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)


In computer vision, video stitching is a very challenging problem. In this paper, we proposed an efficient and effective wide-view video stitching method based on fast structure 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 corresponding seams in the two original images. The seam location of the previous frame is further considered to preserve the interframe 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 feature matching, we propose an efficient algorithm to linearly propagate the deformation vectors to eliminate structure misalignment. 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 initialization 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.
Original languageEnglish
Number of pages13
JournalIEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics
Issue number12
Early online date30 Dec 2014
Publication statusPublished - 2015


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