The Open UniversitySkip to content

Words-of-interest selection based on temporal motion coherence for video retrieval

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 July 2011, Beijing, China.

Full text available as:
PDF (Version of Record) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (434Kb)
DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


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.

Item Type: Conference Item
Copyright Holders: 2011 The Authors
Extra Information: SIGIR’11, July 24–28, 2011, Beijing, China.
ACM 978-1-4503-0757-4/11/07
Keywords: Bag of Visual Words; words-of-interest; video retrieval; temporal motion coherence
Academic Unit/Department: Mathematics, Computing and Technology > Computing & Communications
Mathematics, Computing and Technology
Item ID: 33903
Depositing User: Dawei Song
Date Deposited: 21 Jun 2012 08:54
Last Modified: 23 Feb 2016 23:30
Share this page:


Scopus Citations

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

▼ Automated document suggestions from open access sources

Actions (login may be required)

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340