Event Detection and Analysis from Video Streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
An APRIORI-based Method for Frequent Composite Event Discovery in Videos
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
Applying 3D human model in a posture recognition system
Pattern Recognition Letters
Video understanding for complex activity recognition
Machine Vision and Applications
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EURASIP Journal on Applied Signal Processing
Ontology based complex object recognition
Image and Vision Computing
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IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
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ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
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ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Improving user verification by implementing an agent-based security system
Journal of Ambient Intelligence and Smart Environments
Logic-based representation, reasoning and machine learning for event recognition
Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems
On complex event processing for real-time situational awareness
RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
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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.