Float Greedy-search-based Subspace Clustering

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	Float Greedy-search-based Subspace Clustering
	Lingxiao Ling1,2 ; Man Zhang1,2 ; Qi Li1,2 ; Zhenan Sun1,2,3 ; Ran He(赫然)1,2,3 ; Song, Lingxiao
	2015
会议名称	Asian Conference on Pattern Recognition (ACPR)
会议录名称	Proceedings of the IAPR Asian Conference on Pattern Recognition
会议日期	2015-11
会议地点	Kuala Lumpur, Malaysia
摘要	Many kinds of efficient greedy subspace clustering methods have been proposed to cut down the computation time in clustering large-scale multimedia datasets. However, these methods are easy to fall into local optimum due to the inherent characteristic of greedy algorithms, which are stepoptimal only. To alleviate this problem, this paper proposes a novel greedy subspace clustering strategy based on floating search, called Float Greedy Subspace Clustering (FloatGSC). In order to control the complexity, the nearest subspace neighbor is added in a greedy way, and the subspace is updated by adding an orthogonal basis involved with the newly added data points in each iteration. Besides, a backtracking mechanism is introduced after each iteration to reject wrong neighbors selected in previous iterations. Extensive experiments on motion segmentation and face clustering show that our algorithm can significantly improve the clustering accuracy without sacrificing much computational time, compared with previous greedy subspace clustering methods.
关键词	Subspace Clustering Floating Search
收录类别	EI
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/11624
专题	智能感知与计算研究中心
通讯作者	Song, Lingxiao
作者单位	1.Center for Research on Intelligent Perception and Computing, CASIA 2.National Laboratory of Pattern Recognition, CASIA 3.Center for Excellence in Brain Science and Intelligence Technology, CAS
第一作者单位	模式识别国家重点实验室; 中国科学院自动化研究所
推荐引用方式 GB/T 7714	Lingxiao Ling,Man Zhang,Qi Li,et al. Float Greedy-search-based Subspace Clustering[C],2015.

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