Recurrent Bayesian Network for the Recognition of Human Behaviors from Video


We propose an original bayesian approach to recognize human behaviors from video streams. Mobile objects and their visual features are computed by a vision module. Then, using a Recurrent Bayesian Network, behaviors of the mobile objects are recognized through the temporal evolution of their visual features. 
DOI: 10.1007/3-540-36592-3_7


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