Efficient Fisher Discrimination Dictionary Learning

doi:10.1016/j.sigpro.2016.03.013

CSpace > 应用数学研究所

	Efficient Fisher Discrimination Dictionary Learning
	Jiang, Rui 1; Qiao, Hong 1,2; Zhang, Bo3,4
	2016-11-01
发表期刊	SIGNAL PROCESSING
ISSN	0165-1684
卷号	128 页码:28-39
摘要	Fisher 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.
关键词	Fisher discrimination dictionary learning Nesterov's accelerated gradient method Face recognition Domain adaptation
DOI	10.1016/j.sigpro.2016.03.013
语种	英语
资助项目	National 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研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:000379706500004
出版者	ELSEVIER SCIENCE BV
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/23115
专题	应用数学研究所
通讯作者	Qiao, Hong
作者单位	1.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
推荐引用方式 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.