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Near-duplicate Video Retrieval: Current Research and Future Trends

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5 Author(s)
Shen, H.T. ; The University of Queensland, Brisbane ; Liu, J. ; Huang, Z. ; Ngo, C.-W.
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The exponential growth of online videos, along with the increasing user involvements to video-related activities, has been observed as a constant phenomenon during last decade. User's time spent on video capturing, editing, uploading, searching and viewing has boosted to an unprecedented level. The massive publishing and sharing of videos has given rise to the existence of a already-large amount of near-duplicate content. This imposes urgent demands on near-duplicate video retrieval as a key role in novel tasks such as video search, video copyright protection, video recommendation, and many more. Driven by its significance, near-duplicate video retrieval has recently attracted lots of attention. As discovered in recent works, latest improvements and progresses in near-duplicate video retrieval as well as related topics including low-level feature extraction, signature generation and high-dimensional indexing, are employed to assist the process. As we survey the works in near-duplicate video retrieval, we comparatively investigate existing variants of the definition of near-duplicate video, describe a generic framework, summarize state-of-the-art practices, and explore the emerging trends of this research topic.

Note: Document Withdrawn from IEEE Xplore. The document that would normally appear here has been withdrawn at the request of the authors. Reasonable effort should be made to remove all references to this document. We regret any inconvenience.  

Published in:

MultiMedia, IEEE  (Volume:PP ,  Issue: 99 )

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