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Visual Group Binary Signature for Video Copy Detection

Ozkan, Savas
Esen, Ersin
Akar, Gözde
Need for automatic video copy detection is increased with the recent technical developments in the internet technologies and video recording. Even though image-based techniques with bag-of-word kind of representations are accepted as the best solution because of robustness and speed; they discard the convenient geometric relation which exists among interest points. In this work, we propose a novel geometric relation which computes a binary signature leveraging existence and non-existence of interest points in the neighborhood area. The experimental results on TRECVID 2009 content-based video copy detection dataset show that combination of our method with recently proposed quantization-based indexing and weak geometric consistency schemes outperforms classical representations.