Motion Vector Based Features for Content Based Video Copy Detection

Authors:
Kasim Tasdemir;A. Enis Cetin
Affiliations:
-;-
Venue:
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Year:
2010

Citing 0
Cited 3

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ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)

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Abstract

In this article, we propose a motion vector based feature set for Content Based Copy Detection (CBCD) of video clips. Motion vectors of image frames are one of the signatures of a given video. However, they are not descriptive enough when consecutive image frames are used because most vectors are too small. To overcome this problem we calculate motion vectors in a lower frame rate than the actual frame rate of the video. As a result we obtain longer vectors which form a robust parameter set representing a given video. Experimental results are presented.