Knowledge Commons of Institute of Automation,CAS
Learning low-rank representations with classwise block-diagonal structure for robust face recognition | |
Li, Yong1![]() ![]() ![]() ![]() | |
2014 | |
会议名称 | AAAI |
会议录名称 | AAAI Conference on Artificial Intelligence |
页码 | 2810-2816 |
会议日期 | 2014 |
会议地点 | Québec, Canada |
摘要 |
Face recognition has been widely studied due to its importance in various applications. However, the case that both training images and testing images are corrupted is not well addressed. Motivated by the success of low-rank matrix recovery, we propose a novel semi-supervised low-rank matrix recovery algorithm for robust face recognition. The proposed method can learn robust discriminative representations for both training images and testing images simultaneously by exploiting the classwise block-diagonal structure. Specifically, low-rank matrix approximation can handle the possible contamination of data. Moreover, the classwise block-diagonal structure is exploited to promote discrimination of representations for robust recognition. The above issues are formulated into a unified objective function and we design an efficient optimization procedure based on augmented Lagrange multiplier method to solve it. Extensive experiments on three public databases are performed to validate the effectiveness of our approach. The strong identification capability of representations with block-diagonal structure is verified.
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关键词 | Classwise Block-diagonal Structure Low-rank Representation |
收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/4692 |
专题 | 紫东太初大模型研究中心_图像与视频分析 |
通讯作者 | Li, Yong |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.School of Computer Science, Nanjing University of Science and Technology 3.University of Maryland, College Park |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Li, Yong,Liu, Jing,Li, Zechao,et al. Learning low-rank representations with classwise block-diagonal structure for robust face recognition[C],2014:2810-2816. |
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Learning low-rank re(950KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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