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Improving the Accuracy of Action Classification Using View-Dependent Context Information

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URI: https://hdl.handle.net/10016/18332
ISSN: 0302-9743
ISBN: 978-3-642-21222-2 (online)
ISBN: 978-3-642-21221-5 (print)
DOI: 10.1007/978-3-642-21222-2_17
UXXI: CC/0000017312
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improving_HAIS_LNCS_2011_ps.pdf (593.18 KB)
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2011
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Springer
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This paper presents a human action recognition system that decomposes the task in two subtasks. First, a view-independent classifier, shared between the multiple views to analyze, is applied to obtain an initial guess of the posterior distribution of the performed action. Then, this posterior distribution is combined with view based knowledge to improve the action classification. This allows to reuse the view-independent component when a new view has to be analyzed, needing to only specify the view dependent knowledge. An example of the application of the system into an smart home domain is discussed.
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Proceedings of: 6th International Conference, HAIS 2011, Wroclaw, Poland, May 23-25, 2011
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Human Action Recognition
Bibliographic citation
Corchado, E. et al. (eds.) (2011) Hybrid Artificial Intelligent Systems: 6th International Conference, HAIS 2011, Wroclaw, Poland, May 23-25, 2011, Proceedings, Part II. (Lecture Notes in Computer Science, 6679). Springer, pp. 136- 143.
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