Face Recognition By Combining Cauchy Estimator andDiscriminant Analysis
文献类型：会议论文
| 作者 | Xipeng Yang; Jun Cheng; Wei Feng; Hong Liang; Zhengyao Bai; Dapeng Tao |
| 出版日期 | 2016 |
| 会议名称 | RCAR, 2016 |
| 会议地点 | 柬埔寨 |
| 英文摘要 | Face recognition is a crucial part of object recognition in robot research area, which the scholarly community has shown an intensive attention in the past few years. However, face recognition is still a difficult task since face images are easily confused by changes of the conditions, such as illumination, the different expression, or glasses. The goal of this paper is to address the problem when there are affected images in the dataset. Based on the Cauchy estimator theory and patch alignment framework (PAF), we proposed a dimensional reduction algorithm termed Cauchy estimator discriminant analysis (CEDA) for face recognition. CEDA not only preserves geometry structure of the input samples but also decrease the errors caused by confused samples. Extensive experiments were conducted on the UMIST dataset and demonstrated robustness and effectiveness of the proposed CEDA. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/10157]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2016 |
| 推荐引用方式 GB/T 7714 | Xipeng Yang,Jun Cheng,Wei Feng,et al. Face Recognition By Combining Cauchy Estimator andDiscriminant Analysis[C]. 见:RCAR, 2016. 柬埔寨. |
入库方式： OAI收割
来源：深圳先进技术研究院
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