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Meeting detection in video through semantic analysis

Patino, L. and Ferryman, J. (2015) Meeting detection in video through semantic analysis. In: 12th IEEE International Conference on Advanced Video- and Signal-based Surveillance (AVSS2015), August 25-28, 2015, Karlsruhe, Germany, pp. 1-6.

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In this paper we present a novel approach to detect people meeting. The proposed approach works by translating people behaviour from trajectory information into semantic terms. Having available a semantic model of the meeting behaviour, the event detection is performed in the semantic domain. The model is learnt employing a soft-computing clustering algorithm that combines trajectory information and motion semantic terms. A stable representation can be obtained from a series of examples. Results obtained on a series of videos with different types of meeting situations show that the proposed approach can learn a generic model that can effectively be applied on the behaviour recognition of meeting situations.

Item Type:Conference or Workshop Item (Paper)
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:47388


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