Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Video event detection using motion relativity and visual relatedness
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Video retrieval based on object discovery
Computer Vision and Image Understanding
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Descriptive visual words and visual phrases for image applications
MM '09 Proceedings of the 17th ACM international conference on Multimedia
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The "Bag of Visual Words" (BoW) framework has been widely used in query-by-example video retrieval to model the visual content by a set of quantized local feature descriptors. In this paper, we propose a novel technique to enhance BoW by the selection of Word-of-Interest (WoI) that utilizes the quantified temporal motion coherence of the visual words between the adjacent frames in the query example. Experiments carried out using TRECVID datasets show that our technique improves the retrieval performance of the classical BoW-based approach.