IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Analysis of multi-agent activity using petri nets
Pattern Recognition
Object relevance weight pattern mining for activity recognition and segmentation
Pervasive and Mobile Computing
Statistic-based context recognition in smart car
EuroSSC'09 Proceedings of the 4th European conference on Smart sensing and context
Intent inference via syntactic tracking
Digital Signal Processing
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Applying advanced video technology to understand activity and intent is becoming increasingly important for intelligent video surveillance. We present a general model of a d-level dynamic Bayesian network to perform complex event recognition. The levels of the network are constrained to enforce state hierarchy while the dth level models the duration of simplest event. Moreover, in this paper we propose to use the deterministic annealing clustering method to automatically discover the states for the observable levels. We used real world data sets to show the effectiveness of our proposed method.