Abstract
Object retrieval plays more and more important role as the number of video surveillance systems and the amount of stored data drastically increase. We address in this paper the specific part of retrieving objects of interest within surveillance video sequences problem: relevance feedback. In order to allow users to interact with retrieval system, we propose two relevance feedback methods at object level. These methods take into account appearance as well as temporal aspects of moving objects in surveillance video sequences. That feature is the main difference between our work and previous works. Experimental results on real surveillance video sequences captured in a metro station have proved the performance of two proposed methods.
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References
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Le, TL. (2011). Relevance Feedback for Surveillance Video Retrieval at Object Level. In: Park, J.J., Yang, L.T., Lee, C. (eds) Future Information Technology. Communications in Computer and Information Science, vol 185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22309-9_21
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DOI: https://doi.org/10.1007/978-3-642-22309-9_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22308-2
Online ISBN: 978-3-642-22309-9
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