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ECCV
2010
Springer

Anomalous Behaviour Detection using Spatiotemporal Oriented Energies, Subset Inclusion Histogram Comparison and Event-Driven Pro

9 years 4 months ago
Anomalous Behaviour Detection using Spatiotemporal Oriented Energies, Subset Inclusion Histogram Comparison and Event-Driven Pro
Abstract. This paper proposes a novel approach to anomalous behaviour detection in video. The approach is comprised of three key components. First, distributions of spatiotemporal oriented energy are used to model behaviour. This representation can capture a wide range of naturally occurring visual spacetime patterns and has not previously been applied to anomaly detection. Second, a novel method is proposed for comparing an automatically acquired model of normal behaviour with new observations. The method accounts for situations when only a subset of the model is present in the new observation, as when multiple activities are acceptable in a region yet only one is likely to be encountered at any given instant. Third, event driven processing is employed to automatically mark portions of the video stream that are most likely to contain deviations from the expected and thereby focus computational efforts. The approach has been implemented with real-time performance. Quantitative and qual...
Added 03 Sep 2010
Updated 03 Sep 2010
Type Conference
Year 2010
Where ECCV
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