M. Rombaut

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This paper focuses on human behavior recognition where the main problem is to bridge the semantic gap between the analogue observations of the real world and the symbolic world of human interpretation. For that, a fusion architecture based on the Transfer-able Belief Model framework is proposed and applied to action recognition of an athlete in video(More)
In this paper, a generic architecture based on the Transferable Belief Model (TBM) is proposed for on line and automatic human action and activity recognition in videos of athletics sports with moving camera. The first contribution of this paper is a tool called Belief Scheduler which makes belief on actions smoother, separates actions states (true or(More)
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