Efficient spatiotemporal-attention-driven shot matching
Proceedings of the 15th international conference on Multimedia
An integrated approach to video retrieval
ADC '08 Proceedings of the nineteenth conference on Australasian database - Volume 75
Clip based video summarization and ranking
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Bounded coordinate system indexing for real-time video clip search
ACM Transactions on Information Systems (TOIS)
Key frame vector and its application to shot retrieval
IMCE '09 Proceedings of the 1st international workshop on Interactive multimedia for consumer electronics
Taxonomy of directing semantics for film shot classification
IEEE Transactions on Circuits and Systems for Video Technology
An efficient video indexing and retrieval algorithm using the luminance field trajectory modeling
IEEE Transactions on Circuits and Systems for Video Technology
A video retrieval algorithm using random projections
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
k-Partite graph reinforcement and its application in multimedia information retrieval
Information Sciences: an International Journal
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In this paper, we propose a fast coarse-to-fine video retrieval scheme using shot-level spatio-temporal statistics. The scheme consists of a two-step coarse search followed by a fine search. In the coarse search stage, the shot-level motion and color distribution is computed as spatio-temporal features for shot matching. The first-step coarse search uses the shot-level global statistics to reduce the size of the search space drastically. By adding an adjacent shot of the first query shot, the second-step coarse search introduces a "causality" relation between two consecutive shots to improve the search accuracy. Finally, the fine-search step refines the search result by using the local color features extracted from the key frames of the query shots. Our experimental results show that the proposed method achieves good retrieval performance with a much reduced complexity compared to single-pass methods.