Abstract
Video synopsis is an effective solution for fast browsing and retrieval of long surveillance videos. It aims to shorten long video sequences into its equivalent compact video representation by rearranging the video events in the temporal domain and/or spatial domain. Conventional video synopsis methods focus on reducing the collisions between tubes and maintaining their chronological order, which may alter the original interactions between tubes due to improper tube rearrangement. In this paper, we present an approach to preserve the relationships among tubes (tracks of moving objects) of the original video in the synopsis video. First, a recursive tube-grouping algorithm is proposed to determine the behavior interactions among tubes in a video and group the related tubes together to form tube sets. Second, to preserve the discovered relationships, a spatio-temporal cube voting algorithm is proposed. This cube voting method optimally rearranges the tube sets in the synopsis video, minimizing false collisions between tubes. Third, a method to estimate the duration of the synopsis video is proposed based on an entropy measure of tube collisions. The extensive experimental results demonstrate that the proposed video synopsis framework condenses videos by preserving the original tube interactions and reducing false tube collisions.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
