In this paper, we present an overview of a hybrid approach for event detection from video surveillance sequences that has been developed within the REGIMVid project. This system can be used to index and search the video sequence by the visual content. The platform provides moving object segmentation and tracking, High-level feature extraction and video event detection.We describe the architecture of the system as well as providing an overview of the descriptors supported to date. We then demonstrate the usefulness of the toolbox in the context of feature extraction, events learning and detection in large collection of video surveillance dataset. © 2010 Springer-Verlag.
CITATION STYLE
Wali, A., Ben Aoun, N., Karray, H., Ben Amar, C., & Alimi, A. M. (2010). A new system for event detection from video surveillance sequences. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6475 LNCS, pp. 110–120). https://doi.org/10.1007/978-3-642-17691-3_11
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