International Journal of Computer Vision
A new approach to retrieve video by example video clip
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 2)
Key-frame extraction and shot retrieval using nearest feature line (NFL)
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
Content-based video similarity model
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Motion-Based Video Representation for Scene Change Detection
International Journal of Computer Vision
Multimedia Systems - Special section on video libraries
Fast and robust short video clip search using an index structure
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Latent semantic analysis for an effective region-based video shot retrieval system
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
ClassView: hierarchical video shot classification, indexing, and accessing
IEEE Transactions on Multimedia
ViBE: a compressed video database structured for active browsing and search
IEEE Transactions on Multimedia
Video partitioning by temporal slice coherency
IEEE Transactions on Circuits and Systems for Video Technology
Clip-based similarity measure for query-dependent clip retrieval and video summarization
IEEE Transactions on Circuits and Systems for Video Technology
Key frame vector and its application to shot retrieval
IMCE '09 Proceedings of the 1st international workshop on Interactive multimedia for consumer electronics
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This paper proposes a new approach for shot-based retrieval by optimal matching (OM), which provides an effective mechanism for the similarity measure and ranking of shots by one-to-one matching. In the proposed approach, a weighted bipartite graph is constructed to model the color similarity between two shots. Then OM based on Kuhn---Munkres algorithm is employed to compute the maximum weight of a constructed bipartite graph as the shot similarity value by one-to-one matching among frames. To improve the speed efficiency of OM, two improved algorithms are also proposed: bipartite graph construction based on subshots and bipartite graph construction based on the same number of keyframes. Besides color similarity, motion feature is also employed for shot similarity measure. A motion histogram is constructed for each shot, the motion similarity between two shots is then measured by the intersection of their motion histograms. Finally, the shot similarity is based on the linear combination of color and motion similarity. Experimental results indicate that the proposed approach achieves better performance than other methods in terms of ranking and retrieval capability.