Subspace Clustering by Integrating Sparseness and Spatial-Closeness Priors

doi:10.1088/1742-6596/1631/1/012145

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 机器人视觉团队

	Subspace Clustering by Integrating Sparseness and Spatial-Closeness Priors
	Li,Zhe 5; Pei,Haodong 1,4; He,Liang 5; Liu,Jiaming 5; Hu,Jiaxin 5; Wang,Dongji 2,3
刊名	Journal of Physics: Conference Series
	2020-09-01
卷号	1631 期号:1
ISSN号	1742-6588
DOI	10.1088/1742-6596/1631/1/012145
英文摘要	Abstract How to construct an effective sample affinity matrix is an important problem for subspace clustering, and most existing subspace clustering algorithms pursue the affinity matrix in a single space. In this paper, we propose a novel computational framework for subspace clustering, called Complementary Subspace Clustering (CSC) at first, where the affinity matrix is constructed in a pair of complementary spaces which provide different and complementary constraints on the affinity matrix. Many existing structural priors on self representation and dimensionality reduction can be seamlessly integrated into the CSC framework. Then under this framework, we explore a simple and effective subspace clustering algorithm by respectively introducing two basic priors - sparse representation and spatial closeness - into the referred pair of spaces. Moreover, a kernel variant of the proposed clustering algorithm is present. Extensive experimental results demonstrate that although only basic priors are involved, the explored algorithms from the CSC framework can improve the clustering performances significantly when the number of the sample classes is relatively big.
语种	英语
出版者	IOP Publishing
WOS记录号	IOP:1742-6588-1631-1-012145
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42195]
专题	自动化研究所_模式识别国家重点实验室_机器人视觉团队
作者单位	1.Shanghai Institute of Technical Physics of the Chinese Academy of Sciences, Shanghai 200083, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China 3.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 4.Key Laboratory of Intelligent Infrared Perception, Chinese Academy of Sciences, Shanghai 200083, China 5.Futian Power Supply Bureau, Shenzhen Power Supply Bureau Co., Ltd, Shenzhen, Guangdong 518001, China
推荐引用方式 GB/T 7714	Li,Zhe,Pei,Haodong,He,Liang,et al. Subspace Clustering by Integrating Sparseness and Spatial-Closeness Priors[J]. Journal of Physics: Conference Series,2020,1631(1).
APA	Li,Zhe,Pei,Haodong,He,Liang,Liu,Jiaming,Hu,Jiaxin,&Wang,Dongji.(2020).Subspace Clustering by Integrating Sparseness and Spatial-Closeness Priors.Journal of Physics: Conference Series,1631(1).
MLA	Li,Zhe,et al."Subspace Clustering by Integrating Sparseness and Spatial-Closeness Priors".Journal of Physics: Conference Series 1631.1(2020).