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Proceedings Paper

Vehicle-triggered video compression/decompression for fast and efficient searching in large video databases
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Paper Abstract

Video cameras are widely deployed along city streets, interstate highways, traffic lights, stop signs and toll booths by entities that perform traffic monitoring and law enforcement. The videos captured by these cameras are typically compressed and stored in large databases. Performing a rapid search for a specific vehicle within a large database of compressed videos is often required and can be a time-critical life or death situation. In this paper, we propose video compression and decompression algorithms that enable fast and efficient vehicle or, more generally, event searches in large video databases. The proposed algorithm selects reference frames (i.e., I-frames) based on a vehicle having been detected at a specified position within the scene being monitored while compressing a video sequence. A search for a specific vehicle in the compressed video stream is performed across the reference frames only, which does not require decompression of the full video sequence as in traditional search algorithms. Our experimental results on videos captured in a local road show that the proposed algorithm significantly reduces the search space (thus reducing time and computational resources) in vehicle search tasks within compressed video streams, particularly those captured in light traffic volume conditions.

Paper Details

Date Published: 19 March 2013
PDF: 10 pages
Proc. SPIE 8663, Video Surveillance and Transportation Imaging Applications, 86630Q (19 March 2013); doi: 10.1117/12.2002861
Show Author Affiliations
Orhan Bulan, Xerox Research Ctr. (United States)
Edgar A. Bernal, Xerox Research Ctr. (United States)
Robert P. Loce, Xerox Research Ctr. (United States)
Wencheng Wu, Xerox Research Ctr. (United States)


Published in SPIE Proceedings Vol. 8663:
Video Surveillance and Transportation Imaging Applications
Robert Paul Loce; Eli Saber, Editor(s)

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