A Framework for Handling Spatiotemporal Variations in Video Copy Detection

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 tr...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems for video technology 2008-03, Vol.18 (3), p.412-417
Main Authors: CHIU, Chih-Yi, CHEN, Chu-Song, CHIEN, Lee-Feng
Format: Article
Language:English
Subjects:
Applied sciences
Brightness
Computation
Computational efficiency
Content management
Costs
Exact sciences and technology
Histograms
Image processing
Information theory
Information, signal and communications theory
Matching
Materials handling
Motion detection
Near duplicate
Plagiarism
probability modeling and matching
Protection
Reproduction
Robustness
Signal processing
spatiotemporal analysis
Spatiotemporal phenomena
Telecommunications and information theory
Temporal logic
Video data
Watermarking
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Summary: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.
ISSN:1051-8215
1558-2205
DOI:10.1109/TCSVT.2008.918447