Abstract
Extracting automatically the semantics from visual data is a real challenge. We describe in this paper how recent work in cognitive vision leads to significative results in activity recognition for visualsurveillance and video monitoring. In particular we present work performed in the domain of video understanding in our PULSAR team at INRIA in Sophia Antipolis. Our main objective is to analyse in real-time video streams captured by static video cameras and to recognize their semantic content. We present a cognitive vision approach mixing 4D computer vision techniques and activity recognition based on a priori knowledge. Applications in visualsurveillance and healthcare monitoring are shown. We conclude by current issues in cognitive vision for activity recognition.
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