Fast min-hashing indexing and robust spatio-temporal matching for detecting video copies
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A novel video copy detection method based on statistical analysis
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Video copy recognition by oriented PCA and statistical analysis
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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An effective video copy detection framework should be robust against spatial and temporal variations, e.g., changes in brightness and speed. To this end, a content-based approach for video copy detection is proposed. We define the problem as a partial matching problem in a probabilistic model and transform it into a shortest-path problem in a matching graph. To reduce the computation costs of the proposed framework, we introduce some methods that rapidly select key frames and candidate segments from a large amount of video data. The experiment results show that the proposed approach not only handles spatial and temporal variations well, but it also reduces the computation costs substantially.