30 April 2007 A content based video retrieval method for surveillance and forensic applications
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Abstract
The advances in video surveillance technology have lead to the proliferation of surveillance video cameras for the purposes of viewing areas of interest. Counter terrorism and surveillance applications require video forensics capabilities like querying and searching video data for events, people or objects of interest. A human analyst may accurately spot a suspicious activity in a small segment of video. However, due to the large volume of data collected in real-time video surveillance, it is impractical for human analysts to watch or tag the entire video collected as this can lead to human errors, lower throughput and inconsistencies in the level of scrutiny. In this paper, we introduce an ontology-based video retrieval approach, which represents videos with object ontologies and event ontologies, and annotates videos accordingly. We also describe a user-friendly interface for querying surveillance videos using event dictionaries. Our approach leverages the capabilities of ontologies in specifying knowledge at different levels, and, in this way, provides flexibility to a user while forming a query. It is also capable of detecting undefined events such as not previously conceived abnormal events.
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Kalyan Vadakkeveedu, Peng Xu, Ronald Fernandes, Richard J. Mayer, "A content based video retrieval method for surveillance and forensic applications", Proc. SPIE 6560, Intelligent Computing: Theory and Applications V, 656004 (30 April 2007); doi: 10.1117/12.720078; https://doi.org/10.1117/12.720078
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