PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Spatio-Temporal Features for Robust Content-Based Video Copy Detection
Geert Willems, Tinne Tuytelaars and Luc Van Gool
In: MIR 2008(2008).

Abstract

In this paper, we present a new method for robust content- based video copy detection based on local spatio-temporal features. As we show by experimental validation, the use of local spatio-temporal features instead of purely spatial ones brings additional robustness and discriminativity. Efficient operation is ensured by using the new spatio-temporal fea- tures proposed in [20]. To cope with the high-dimensionality of the resulting descriptors, these features are incorporated in a disk-based index and query system based on p-stable locality sensitive hashing. The system is applied to the task of video footage reuse detection in news broadcasts. Results are reported on 88 hours of news broadcast data from the TRECVID2006 dataset.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:5199
Deposited By:Tinne Tuytelaars
Deposited On:24 March 2009