Two-dimensional relaxed representation

	Two-dimensional relaxed representation
	Dong, Qiulei
发表期刊	NEUROCOMPUTING
	2013-12-09
卷号	121 期号:1 页码:248-253
文章类型	Article
摘要	In this paper, a novel classification framework called two-dimensional relaxed representation (2DRR) is proposed for image classification. Different from recent popular vector-based representations with/without sparsity which encode a vector signal as a sparse/nonsparse linear combination of elementary vector signals, 2DRR is based on 2D image matrices, where each column of the input matrix signal is represented by a combination of the corresponding columns of the elementary matrices. In order to preserve the global linear coding relationship between the input matrix and these elementary matrices, the proposed 2DRR constrains the coding coefficients corresponding to each column of the input matrix to be locally close. Then two algorithms are derived from the 2DRR framework under the l(2) norm and the l(1) norm respectively. Extensive experimental results show the effectiveness of the proposed algorithms in comparison to three existing algorithms. (C) 2013 Elsevier B.V. All rights reserved.
关键词	Relaxed Representation Sparsity Image Classification
WOS标题词	Science & Technology ; Technology
关键词[WOS]	FACE RECOGNITION ; SPARSE REPRESENTATION
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000325303800025
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/2991
专题	多模态人工智能系统全国重点实验室_机器人视觉
通讯作者	Dong, Qiulei
作者单位	Chinese Acad Sci, NLPR, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Dong, Qiulei. Two-dimensional relaxed representation[J]. NEUROCOMPUTING,2013,121(1):248-253.
APA	Dong, Qiulei.(2013).Two-dimensional relaxed representation.NEUROCOMPUTING,121(1),248-253.
MLA	Dong, Qiulei."Two-dimensional relaxed representation".NEUROCOMPUTING 121.1(2013):248-253.

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