Proceedings of the ACM International Conference on Image and Video Retrieval
An efficient near-duplicate video shot detection method using shot-based interest points
IEEE Transactions on Multimedia
An analysis of independence of video signatures based on tomography
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Video identification using video tomography
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Mining near-duplicate graph for cluster-based reranking of web video search results
ACM Transactions on Information Systems (TOIS)
Monitoring near duplicates over video streams
Proceedings of the international conference on Multimedia
Video copy detection: sequence matching using hypothesis test
AST/UCMA/ISA/ACN'10 Proceedings of the 2010 international conference on Advances in computer science and information technology
Speeding up complex video copy detection queries
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Near-duplicate video retrieval: Current research and future trends
ACM Computing Surveys (CSUR)
ACM Transactions on Information Systems (TOIS)
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Digital videos are increasingly adopted in various multimedia applications where they are usually broadcasted or transmitted as video streams. Continuously monitoring copies on the fast and long streaming videos is gaining attention due to its importance in content and rights management. The problem of video copies detection on video streams is complicated by two issues. First, original videos may be edited, with their frames being reordered, to avoid detection. Second, there are many concurrent video streams and for each stream, there could be many continuous video copy monitoring queries. Efficient data stream algorithms are therefore essential for processing a large number of continuous queries on video streams. In this paper, we first define video sequence similarity that is robust with respect to changes of videos, and a hash-based video sketch for efficient computation of sequence similarity. We then present a novel bit vector signature of the sketch to achieve two optimization objectives: CPU cost and memory requirement. Finally, in order to handle multiple continuous queries simultaneously, we design an index structure for the query sequences. We implemented the system and use real videos for the experimental study. Experimental results confirm the efficiency and effectiveness of our proposed techniques.