Content Based Video Identification in Peer-to-Peer Networks: Requirements and a Novel Solutions

TitleContent Based Video Identification in Peer-to-Peer Networks: Requirements and a Novel Solutions
Publication TypeJournal Article
Year of Publication2012
AuthorsKoz, A, Lagendijk, RL
Journal(submitted to) IEEE Transactions on Image Processing
Abstract

Content identification in peer-to-peer (P2P) networks has until now been achieved by using metadata or cryptographic hashes. However, with increasing number of duplicates in different names and formats especially in (unmanaged) P2P networks, these tools have become insufficient for proper content finding and access right management. A complementary possible approach is to identify the content in P2P networks by using perceptual hashes (or fingerprints) extracted from the perceptual features of the content robust to typical processing. In this paper, we first discuss the essential differences in fingerprint size, fingerprint extraction complexity, and fingerprint search methodology for a distributed video identification system in P2P networks compared with traditional central database implementations. Then, we propose a novel method optimized for P2P networks that uses only differences of video frame means. The proposed method reduces the fingerprint sizes into kilobytes, extraction time to seconds, and search duration into milliseconds, and achieves more than 90 % detection rates with 1-4 minutes granularities. Furthermore, the uniform distribution of the extracted fingerprints enables the usage of existing DHT-based keyword search mechanisms for fingerprint queries.

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