Abstract
This paper presented a temporal sequence analyzing method, aiming at the extraction of typical sequences from an unlabeled dataset. The extraction procedure is based on HMM training and hierarchical separation of WTOM (Weighted Transition Occurring Matrix). During the extraction, HMMs are built each for a kind of typical sequence. Then Threshold Model is used to segment and recognize continuous sequence. The method has been tested on unsupervised event analysis in video surveillance and model learning of athlete actions.
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© 2004 Springer-Verlag Berlin Heidelberg
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Ma, G., Lin, X. (2004). Typical Sequences Extraction and Recognition. In: Sebe, N., Lew, M., Huang, T.S. (eds) Computer Vision in Human-Computer Interaction. CVHCI 2004. Lecture Notes in Computer Science, vol 3058. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24837-8_7
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DOI: https://doi.org/10.1007/978-3-540-24837-8_7
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