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Vector quantization enhancement for computer vision tasks

Trichet, Remi and O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135 (2016) Vector quantization enhancement for computer vision tasks. In: Advanced Concepts for Intelligent Vision Systems, 2016, 24-27 Oct 2016, Lecce, Italy. ISBN 978-3-319-48679-6

Abstract
This paper augments the Bag-of-Word scheme in several respects: we incorporate a category label into the clustering process, build classifier-tailored codebooks, and weight codewords according to their probability to occur. A size-adaptive feature clustering algorithm is also proposed as an alternative to k-means. Experiments on the PASCAL VOC 2007 challenge validate the approach for classical hardassignment as well as VLAD encoding.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Digital video
Computer Science > Image processing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Published in: Advanced Concepts for Intelligent Vision Systems. Lecture Notes in Computer Science (LNCS) 10016. Springer. ISBN 978-3-319-48679-6
Publisher:Springer
Official URL:http://dx.doi.org/10.1007/978-3-319-48680-2_35
Copyright Information:© 2016 Springer.The original publication is available at www.springerlink.com
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland SFI/12/RC/2289
ID Code:21349
Deposited On:27 Oct 2016 10:27 by Noel Edward O'connor . Last Modified 19 Oct 2018 09:25
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