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Evaluation of key frame-based retrieval techniques for video

Pickering, Marcus and Rüger, Stefan (2003). Evaluation of key frame-based retrieval techniques for video. Computer Vision and Image Understanding, 92(2-3) pp. 217–235.

DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1016/j.cviu.2003.06.002
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Abstract

We investigate the application of a variety of content-based image retrieval techniques to the problem of video retrieval. We generate large numbers of features for each of the key frames selected by a highly effective shot boundary detection algorithm to facilitate a query by example type search. The retrieval performance of two learning methods, boosting and k-nearest neighbours, is compared against a vector space model. We carry out a novel and extensive evaluation to demonstrate and compare the usefulness of these algorithms for video retrieval tasks using a carefully created test collection of over 6000 still images, where performance is measured against relevance judgements based on human image annotations. Three types of experiment are carried out: classification tasks, category searches (both related to automated annotation and summarisation of video material) and real world searches (for navigation and entry point finding). We also show graphical results of real video search tasks using the algorithms, which have not previously been applied to video material in this way.

Item Type: Journal Article
ISSN: 1077-3142
Academic Unit/Department: Knowledge Media Institute
Item ID: 8045
Depositing User: Users 7283 not found.
Date Deposited: 12 Jun 2007
Last Modified: 04 Apr 2011 09:22
URI: http://oro.open.ac.uk/id/eprint/8045
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