Unsupervised Activity Extraction on Long-Term Video Recordings employing Soft Computing Relations

Abstract : In this work we present a novel approach for activity extraction and knowledge discovery from video employing fuzzy relations. Spatial and temporal properties from detected mobile objects are modeled with fuzzy relations. These can then be aggregated employing typical soft-computing algebra. A clustering algorithm based on the transitive closure calculation of the fuzzy relations allows finding spatio-temporal patterns of activity. We present results obtained on videos corresponding to different sequences of apron monitoring in the Toulouse airport in France.
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https://hal.inria.fr/hal-00650048
Contributor : Jose Luis Patino Vilchis <>
Submitted on : Friday, December 9, 2011 - 12:33:56 PM
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Jose Luis Patino Vilchis, Murray Evans, James Ferryman, François Bremond, Monique Thonnat. Unsupervised Activity Extraction on Long-Term Video Recordings employing Soft Computing Relations. 8th International Conference on Computer Vision Systems, ICVS 2011, Sep 2011, Sophia Antipolis, France. ⟨hal-00650048⟩

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