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Anomalous behaviour detection using spatiotemporal oriented energies, subset inclusion histogram comparison and event driven processing (2010)
| Venue: | ECCV |
| Citations: | 14 - 6 self |
BibTeX
@MISC{Zaharescu10anomalousbehaviour,
author = {Andrei Zaharescu and Richard Wildes},
title = { Anomalous behaviour detection using spatiotemporal oriented energies, subset inclusion histogram comparison and event driven processing },
year = {2010}
}
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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 qualitative empirical evaluation on a challenging set of natural image videos demonstrates the approach’s superior performance relative to various alternatives.
Keyphrases
anomalous behaviour detection inclusion histogram comparison new observation computational effort normal behaviour natural image video visual spacetime pattern multiple activity superior performance relative qualitative empirical evaluation event driven processing various alternative novel approach key component video stream wide range real-time performance method account challenging set novel method
