A joint optimization framework of low-dimensional projection and collaborative representation for discriminative classification |
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Author: | Liu, Xiaofeng1,2,3; Li, Zhaofeng2,3,4; Kong, Lingsheng2; |
Organizations: |
1Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA 2Changchun institute of optical precision machinery and physics, Chinese academy of sciences, CAS, Changchun, China 3University of Chinese Academy of Sciences, Beijing, China
4Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
5Viterbi school of engineering, University of Southern California, Los Angeles, USA 6Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 0.8 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2019062722214 |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers,
2018
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Publish Date: | 2019-06-27 |
Description: |
AbstractVarious representation-based methods have been developed and shown great potential for pattern classification. To further improve their discriminability, we propose a Bi-level optimization framework in terms of both low-dimensional projection and collaborative representation. Specifically, during the projection phase, we try to minimize the intra-class similarity and inter-class dissimilarity, while in the representation phase, our goal is to achieve the lowest correlation of the representation results. Solving this joint optimization mutually reinforces both aspects of feature projection and representation. Experiments on face recognition, object categorization and scene classification dataset demonstrate remarkable performance improvements led by the proposed framework. see all
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ISBN: | 978-1-5386-3788-3 |
ISBN Print: | 978-1-5386-3789-0 |
Pages: | 1493 - 1498 |
DOI: | 10.1109/ICPR.2018.8545267 |
OADOI: | https://oadoi.org/10.1109/ICPR.2018.8545267 |
Host publication: |
2018 24th International Conference on Pattern Recognition (ICPR) |
Conference: |
International Conference on Pattern Recognition |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Copyright information: |
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