CSpace  > 应用数学研究所
Efficient Fisher Discrimination Dictionary Learning
Jiang, Rui1; Qiao, Hong1,2; Zhang, Bo3,4
2016-11-01
Source PublicationSIGNAL PROCESSING
ISSN0165-1684
Volume128Pages:28-39
AbstractFisher Determination Dictionary Learning (FDDL) has shown to be effective in image classification. However, the Original FDDL (O-FDDL) method is time-consuming. To address this issue, a fast Simplified FDDL (S-FDDL) method was proposed. But S-FDDL ignores the role of collaborative reconstruction, thus having an unstable performance in classification tasks with unbalanced changes in different classes. This paper focuses on developing an Efficient FDDL (E-FDDL) method, which is more suitable for such classification problems. Precisely, instead of solving the original Fisher Discrimination based Sparse Representation (FDSR) problem, we propose to solve an Approximate FDSR (A-FDSR) problem whose objective function is an upper bound of that of FDSR. A-FDSR considers the role of both the discriminative reconstruction and the collaborative reconstruction. This makes E-FDDL stable when dealing with classification tasks with unbalanced changes in different classes. Furthermore, fast optimization strategies are applicable to A-FDSR, thus leading to the high efficiency of E-FDDL which can be explained by analysis on convergence rate and computational complexity. We also use E-FDDL to accelerate the Shared Domain-adapted Dictionary Learning (SDDL) algorithm which is a FDDL based new method for domain adaptation. Experimental results on face and object recognition demonstrate the stable and fast performance of E-FDDL. (C) 2016 Elsevier B.V. All rights reserved.
KeywordFisher discrimination dictionary learning Nesterov's accelerated gradient method Face recognition Domain adaptation
DOI10.1016/j.sigpro.2016.03.013
Language英语
Funding ProjectNational Natural Science Foundation of China[61210009] ; National Natural Science Foundation of China[61033011] ; National Natural Science Foundation of China[61379093] ; National Natural Science Foundation of China[11131006]
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000379706500004
PublisherELSEVIER SCIENCE BV
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/23115
Collection应用数学研究所
Corresponding AuthorQiao, Hong
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Chinese Acad Sci, CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China
3.Chinese Acad Sci, LSEC, Beijing 100190, Peoples R China
4.Chinese Acad Sci, AMSS, Inst Appl Math, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Jiang, Rui,Qiao, Hong,Zhang, Bo. Efficient Fisher Discrimination Dictionary Learning[J]. SIGNAL PROCESSING,2016,128:28-39.
APA Jiang, Rui,Qiao, Hong,&Zhang, Bo.(2016).Efficient Fisher Discrimination Dictionary Learning.SIGNAL PROCESSING,128,28-39.
MLA Jiang, Rui,et al."Efficient Fisher Discrimination Dictionary Learning".SIGNAL PROCESSING 128(2016):28-39.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Jiang, Rui]'s Articles
[Qiao, Hong]'s Articles
[Zhang, Bo]'s Articles
Baidu academic
Similar articles in Baidu academic
[Jiang, Rui]'s Articles
[Qiao, Hong]'s Articles
[Zhang, Bo]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Jiang, Rui]'s Articles
[Qiao, Hong]'s Articles
[Zhang, Bo]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.