Fast Online Video Synopsis Based on Potential Collision Graph
Yi He, Zhiguo Qu, Changxin Gao, Nong Sang · IEEE Signal Processing Letters · 2016
Video synopsis is a smart solution to fast browsing and retrieval of raw surveillance data, in which tube rearrangement plays a key role. However, conventional methods for tube rearrangement are based on minimizing a global energy function, which is computational intensive and time consuming. In this letter, we propose a novel tube rearrangement strategy for online video synopsis by analyzing collision relationship between tubes. A potential collision graph (PCG) is constructed to represent the tubes and their potential collision relationship. Based on the PCG, tube rearrangement is achieved by filling the tubes into synopsis video in a deterministic way, which decreases computational complexity. Finally, we incorporate the proposed tube rearrangement into an online framework to generate video synopsis and validate its efficiency with extensive experiments.