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Measuring the influence of concept detection on video retrieval

Toharia, Pablo, Robles, Oscar D., Smeaton, Alan F. and Rodríguez, Ángel (2009) Measuring the influence of concept detection on video retrieval. In: CAIP 2009 - 13th International Conference on Computer Analysis of Images and Patterns, 2-4 September 2009, Münster (North Rhine-Westphalia), Germany. ISBN 978-3-642-03766-5

Abstract
There is an increasing emphasis on including semantic concept detection as part of video retrieval. This represents a modality for retrieval quite different from metadata-based and keyframe similarity-based approaches. One of the premises on which the success of this is based, is that good quality detection is available in order to guarantee retrieval quality. But how good does the feature detection actually need to be? Is it possible to achieve good retrieval quality, even with poor quality concept detection and if so then what is the 'tipping point' below which detection accuracy proves not to be beneficial? In this paper we explore this question using a collection of rushes video where we artificially vary the quality of detection of semantic features and we study the impact on the resulting retrieval. Our results show that the impact of improving or degrading performance of concept detectors is not directly reflected as retrieval performance and this raises interesting questions about how accurate concept detection really needs to be.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Additional Information:http://cvpr.uni-muenster.de/CAIP2009/
Uncontrolled Keywords:evaluation; semantic concepts;
Subjects:Engineering > Signal processing
Computer Science > Information retrieval
Computer Science > Digital video
Computer Science > Image processing
DCU Faculties and Centres:Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: Computer Analysis of Images and Patterns. Lecture Notes in Computer Science 5702. Springer Berlin / Heidelberg. ISBN 978-3-642-03766-5
Publisher:Springer Berlin / Heidelberg
Official URL:http://dx.doi.org/10.1007/978-3-642-03767-2_71
Copyright Information:© 2009 Springer
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Spanish Ministry of Education and Science, Science Foundation Ireland
ID Code:4607
Deposited On:17 Jun 2009 10:13 by Alan Smeaton . Last Modified 19 Jul 2018 14:44
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