Discriminative Representative Selection via Structure Sparsity
文献类型：会议论文
| 作者 | Wang, Baoxing; Yin, Qiyue ; Wu, Shu; Wang, Liang
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| 出版日期 | 2014 |
| 会议日期 | August 24-28 |
| 会议地点 | Stockholm |
| 关键词 | Representative Selection Structure Sparsity |
| 英文摘要 | This paper focuses on the problem of finding a few representatives for a given dataset, which have both representation and discrimination ability. To solve this problem, we propose a novel algorithm, called Structure Sparsity based Discriminative Representative Selection (SSDRS), to find a representative subset of data points. The selected representative subset keeps the representation ability based on sparse representation models assuming that each data point can be expressed as a linear combination of those representatives. Meanwhile, we employ the Fisher discrimination criterion to make the coefficient matrix possess small within-class scatter but big between-class scatter, which leads to the discriminant ability of representatives. Since such a selected subset is representative and discriminative, it can be used to properly describe the entire dataset and achieve a good classification performance simultaneously. Experimental results in terms of video summarization and image classification indicate that our proposed algorithm outperforms the state-ofthe-art methods. |
| 会议录 | In Proceedings of the 22nd International Conference on Pattern Recognition (ICPR) 2014
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12349]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Wu, Shu |
| 推荐引用方式 GB/T 7714 | Wang, Baoxing,Yin, Qiyue,Wu, Shu,et al. Discriminative Representative Selection via Structure Sparsity[C]. 见:. Stockholm. August 24-28. |
入库方式： OAI收割
来源：自动化研究所
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