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A Survey on Visual Content-Based Video Indexing and Retrieval

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5 Author(s)
Weiming Hu ; Nat. Lab. of Pattern Recognition, Chinese Acad. of Sci., Beijing, China ; Nianhua Xie ; Li Li ; Xianglin Zeng
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Video indexing and retrieval have a wide spectrum of promising applications, motivating the interest of researchers worldwide. This paper offers a tutorial and an overview of the landscape of general strategies in visual content-based video indexing and retrieval, focusing on methods for video structure analysis, including shot boundary detection, key frame extraction and scene segmentation, extraction of features including static key frame features, object features and motion features, video data mining, video annotation, video retrieval including query interfaces, similarity measure and relevance feedback, and video browsing. Finally, we analyze future research directions.

Published in:

Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on  (Volume:41 ,  Issue: 6 )

Date of Publication:

Nov. 2011

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