Video manifold modelling: finding the right parameter settings for anomaly detection
Pages 168 - 173
Abstract
Using video manifold to analyze video scenes and detect possible anomaly has become a popular research topic in recent years. While a number of attempts have been proposed and reported promising outcomes, there is currently a lack of understanding about the parameter setting for various components in the algorithmic framework. In this paper we look at some key parameters, particularly the dimension of the video manifold, the embedding dimension of the video trajectory, and explore the plausibility of setting these parameters automatically using outcome of spectral clustering and fractal dimension analysis. Experiments are conducted using a benchmark dataset and the results are promising.
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Index Terms
- Video manifold modelling: finding the right parameter settings for anomaly detection
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- Dept. of Information Science, Univ.of Otago: Department of Information Science, University of Otago, Dunedin, New Zealand
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Published: 26 November 2012
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