Abstract
This paper proposes an approach for retrieving videos based on object trajectories and subtrajectories. First, trajectories are segmented into subtrajectories according to the characteristics of the movement. Efficient trajectory segmentation relies on a symbolic representation and uses selected control points along the trajectory. The selected control points with high curvature capture the trajectory various geometrical and syntactic features. This symbolic representation, beyond the initial numeric representation, does not suffer from scaling, translation or rotation. Then, in order to compare trajectories based on their subtrajectories, several matching strategies are possible, according to the retrieval goal from the user. Moreover, trajectories can be represented at the numeric, symbolic or the semantic level, with the possibility to go easily from one representation to another. This approach for indexing and retrieval has been tested with a database containing 2500 trajectories, with promising results.
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References
Chenn, W., Chang, S.F.: Motion trajectory matching of video objects. In: SPIE 2003 (2003)
Bashir, F.: Object Motion Trajectory-Based Video Database System Indexing, Retrieval, Classification, and Recognition. PHD Thesis of Electrical and Computer Engineering, College of Engineering, University of Illinois Chicago (2005)
Piciarelli, C., Foresti, G.L., Snidara, L.: Trajectory clustering and its applications for video surveillance. In: Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, pp. 40–45 (2005)
Hsieh, J.W., Yu, S.L., Chen, Y.S.: Motion-Based Video Retrieval by Trajectory Matching. In: Proc IEEE Trans. on Circuits and Systems for Video Technology, March 2006, vol. 16(3) (2006)
Chen, L., Os̈u, M.T., Oria, V.: Symbolic Representation and Retrieval of Moving Object Trajectories. In: MIR 2004, NewYork, pp. 15–16 (2004)
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© 2006 Springer-Verlag Berlin Heidelberg
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Le, TL., Boucher, A., Thonnat, M. (2006). Subtrajectory-Based Video Indexing and Retrieval. In: Cham, TJ., Cai, J., Dorai, C., Rajan, D., Chua, TS., Chia, LT. (eds) Advances in Multimedia Modeling. MMM 2007. Lecture Notes in Computer Science, vol 4351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69423-6_41
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DOI: https://doi.org/10.1007/978-3-540-69423-6_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69421-2
Online ISBN: 978-3-540-69423-6
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