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http://dx.doi.org/10.14400/JDC.2022.20.1.179

Efficient video matching method for illegal video detection  

Choi, Minseok (Division of AI Informatics, Sahmyook University)
Publication Information
Journal of Digital Convergence / v.20, no.1, 2022 , pp. 179-184 More about this Journal
Abstract
With the development of information and communication technology, the production and distribution of digital contents is rapidly increasing, and the distribution of illegally copied contents also increases, causing various problems. In order to prevent illegal distribution of contents, a DRM (Digital Rights Management)-based approach can be used, but in a situation where the contents are already copied and distributed, a method of searching and detecting the duplicated contents is required. In this paper, a duplication detection method based on the contents of video content is proposed. The proposed method divides the video into scene units using the visual rhythm extracted from the video, and hierarchically applies the playback time and color feature values of each divided scene to quickly and efficiently detect duplicate videos in a large database. Through experiments, it was shown that the proposed method can reliably detect various replication modifications.
Keywords
Video matching; Copy detection; Content-based retrieval; Visual rhythm; Dominant color;
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Times Cited By KSCI : 8  (Citation Analysis)
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