Float Greedy-search-based Subspace Clustering

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	Float Greedy-search-based Subspace Clustering
	Lingxiao Ling 1,2; Man Zhang1,2 ; Qi Li1,2 ; Zhenan Sun1,2,3 ; Ran He(赫然)1,2,3 ; Song, Lingxiao
	2015
会议日期	2015-11
会议地点	Kuala Lumpur, Malaysia
关键词	Subspace Clustering Floating Search
英文摘要	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.
会议录	Proceedings of the IAPR Asian Conference on Pattern Recognition
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/11624]
专题	自动化研究所_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
推荐引用方式 GB/T 7714	Lingxiao Ling,Man Zhang,Qi Li,et al. Float Greedy-search-based Subspace Clustering[C]. 见:. Kuala Lumpur, Malaysia. 2015-11.