Fast and robust short video clip search using an index structure
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
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Proceedings of the 6th ACM international conference on Image and video retrieval
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ADC '08 Proceedings of the nineteenth conference on Australasian database - Volume 75
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CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
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AREA '08 Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams
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ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
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PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
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MIV'05 Proceedings of the 5th WSEAS international conference on Multimedia, internet & video technologies
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ECDL'06 Proceedings of the 10th European conference on Research and Advanced Technology for Digital Libraries
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PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
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DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Fast and robust short video clip search for copy detection
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Near-duplicate video retrieval based on clustering by multiple sequence alignment
Proceedings of the 20th ACM international conference on Multimedia
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In this paper a fast and robust method is proposed to search a large video collection for given short clips. Compared with existing video searching methods which use visual features only, our scheme performs a two-phase hierarchical matching technique using visual and audio features successively. Considering that video sampling rate (25 or 30 fps) is much lower than that of audio (8 to 48 kHz), a coarse search is implemented with sub-sampled video frames first, and then potential matches will be verified and accurately located using fine audio features. Both features are extracted directly from MPEG compressed video for computational efficiency. Experiments have been conducted on over 10.5 hours of video to search for re-occurrences of 83 TV commercials and one news lead-out clip. All the 220 instances are correctly detected with no false alarm. Our experiments also show that the proposed method is robust to variations of video bit rate, frame rate, frame size and color shifting.