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Green Image
Issue No. 10 - Oct. (2013 vol. 19)
ISSN: 1077-2626
pp: 1664-1676
Yongwei Nie , Comput. Sch., Wuhan Univ., Wuhan, China
Chunxia Xiao , Comput. Sch., Wuhan Univ., Wuhan, China
Hanqiu Sun , Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, China
Ping Li , Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, China
Video synopsis aims at providing condensed representations of video data sets that can be easily captured from digital cameras nowadays, especially for daily surveillance videos. Previous work in video synopsis usually moves active objects along the time axis, which inevitably causes collisions among the moving objects if compressed much. In this paper, we propose a novel approach for compact video synopsis using a unified spatiotemporal optimization. Our approach globally shifts moving objects in both spatial and temporal domains, which shifting objects temporally to reduce the length of the video and shifting colliding objects spatially to avoid visible collision artifacts. Furthermore, using a multilevel patch relocation (MPR) method, the moving space of the original video is expanded into a compact background based on environmental content to fit with the shifted objects. The shifted objects are finally composited with the expanded moving space to obtain the high-quality video synopsis, which is more condensed while remaining free of collision artifacts. Our experimental results have shown that the compact video synopsis we produced can be browsed quickly, preserves relative spatiotemporal relationships, and avoids motion collisions.
Spatiotemporal phenomena, Surveillance, Optimization, Visualization, Space vehicles, Context, Trajectory,patch relocation, Video synopsis, surveillance, optimization
Yongwei Nie, Chunxia Xiao, Hanqiu Sun, Ping Li, "Compact Video Synopsis via Global Spatiotemporal Optimization", IEEE Transactions on Visualization & Computer Graphics, vol. 19, no. , pp. 1664-1676, Oct. 2013, doi:10.1109/TVCG.2012.176
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