Content-based video copy detection using spatio-temporal compact feature

Authors:
Joosub Kim;Jeho Nam
Affiliations:
School of Mobile Communication & Digital Broadcasting Eng., Univ. of Science and Techn. and Broadcasting & Telecommunication Media Research Dept., Electronics and Telecommunication Research Instit ...;School of Mobile Communication & Digital Broadcasting Eng., Univ. of Science and Techn. and Broadcasting & Telecommunication Media Research Dept., Electronics and Telecommunication Research Instit ...
Venue:
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 3
Year:
2009

Citing 3
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Abstract

This paper presents a content-based copy detection algorithm that detects online distribution of illegeally copied video. Particularly, the proposed algorithm uses keyframes with abrupt changes of luminance, than extracts spatio-temporal compact features stored in the database of videos, the proposed approach distinguishes whether an uploaded video is illegally copied or not. Note that we analyze only a set of keyframes instead of an entire video frame. thus, it is highly efficient to detect illegal copied video when we handle a vast size of videos. Also, we confirm that the proposed method is robust to a variety of video modification that are often applied by online video redistribution, such as aspect-ratio change, logo insertion, caption insertion, visual quality degradation, and resolution change.