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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
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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