Fast min-hashing indexing and robust spatio-temporal matching for detecting video copies
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Video identification using video tomography
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
A fast video copy detection approach by dynamic programming
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
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In this paper, a novel method is presented to detect video copies for a given video query. These copies and the query have identical or near-duplicate content, which might differ in their spatiotemporal structures slightly. To address both the efficient and effective issues, we conduct the bag-of-words model for video feature representation, and apply a coarse-to-fine matching scheme to analyze the video spatiotemporal structure. The proposed method can deal with various kinds of video transformations, such as cropping, zooming, speed change, and subsequence insertion/deletion, which are not well addressed in existing methods. Besides, two indexing methods are employed to speed up the matching process. Experimental results show that the proposed method can behave in an efficient and effective manner.