Online recognition of group actions in intelligent meeting scenario

Xiang Zhang; Linmi Tao; Guangyou Xu

doi:10.1117/12.760170

28 November 2007 Online recognition of group actions in intelligent meeting scenario

Xiang Zhang, Linmi Tao, Guangyou Xu

Proceedings Volume 6833, Electronic Imaging and Multimedia Technology V; 683312 (2007) https://doi.org/10.1117/12.760170
Event: Photonics Asia 2007, 2007, Beijing, China

Abstract

Group actions play a key role in intelligent meetings. In this paper, we propose a probabilistic approach to online segment meetings as a sequence of group actions, such as monologue, presentation, discussion, and break. In our approach, we decompose group actions into three sub-actions according to three sorts of features independently: audio features, video features and group visual features. In accordance with this assumption state spaces are decomposed into two levels of resolution: meeting actions and meeting sub-actions. Multi-stream dynamic Bayesian network is constructed based on three level state nodes modeling group actions, sub-actions, and three sorts of features. Particle filters are applied to efficiently online recognize group actions, which is based on the estimate of joint posteriors over node states of multi-stream dynamic Bayesian network. Posterior probabilities over all state spaces are represented by temporal sets of their weighted samples. We make seven compared experiments with the different sample numbers of 50,100, 200,300,400, 500 and 600. The recognition accuracy gets higher when there are more sample numbers, but is takes more time for event inference.

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Xiang Zhang, Linmi Tao, and Guangyou Xu "Online recognition of group actions in intelligent meeting scenario", Proc. SPIE 6833, Electronic Imaging and Multimedia Technology V, 683312 (28 November 2007); https://doi.org/10.1117/12.760170

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KEYWORDS

Visualization

Particle filters

Visual process modeling

Cameras

Particles

Video

Feature extraction

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