Words-of-interest selection based on temporal motion coherence for video retrieval
http://data.open.ac.uk/oro/33903
is a Article , Academic article

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Date 2011-07
Is part of repository
Status Peer reviewed
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  • http://data.open.ac.uk/oro/document/62790
  • http://data.open.ac.uk/oro/document/62791
  • http://data.open.ac.uk/oro/document/62792
  • http://data.open.ac.uk/oro/document/63098
Abstract 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.
Authors authors
Type
Label Wang, Lei; Song, Dawei and Elyan, Eyad (2011). Words-of-interest selection based on temporal motion coherence for video retrieval. In: 34th Annual ACM SIGIR Conference (SIGIR'2011), 24-28 Jul 2011, Beijing, China.
Title Words-of-interest selection based on temporal motion coherence for video retrieval
Dataset Open Research Online
Creator
At 34th Annual ACM SIGIR Conference (SIGIR'2011)