| Learning associate appearance manifolds for cross-pose face recognition | |
Xue Chen; Chunheng Wang ; Baihua Xiao; Xinyuan Cai
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| 2014 | |
| 会议名称 | 2014 IEEE International Conference on Image Processing (ICIP) |
| 会议录名称 | International Conference on Image Processing (ICIP) |
| 页码 | 1907-1911 |
| 会议日期 | 2014 |
| 会议地点 | Pairs |
| 摘要 | Pose variation is a major challenge in face recognition. In this paper, we propose a novel cross-pose face recognition method by learning associate appearance manifolds to model the connection of faces under different poses. The associate manifolds are built on an auxiliary set, in which each identity contains cross-pose face images. The basic assumption is that cross-pose face images from two similar identities can be projected onto similar appearance manifolds by pose-specific transforms. We first associate the input faces with alike identities from the auxiliary set. Then the manifolds of cross-pose faces in the training set are confined close to that of the associate identities in the auxiliary set. Thus, the connection of cross-pose faces is well modeled by the associate appearance manifolds on the auxiliary set. Formally, we formulate the assumption as a manifold-based distance minimization problem, so as to learn the optimal transforms. Experiments on the Multi-PIE dataset demonstrate the effectiveness of the proposed method |
| 关键词 | Cross-pose Face Recognition Associate Appearance Manifolds |
| 文献类型 | 会议论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/5147 |
| 专题 | 复杂系统管理与控制国家重点实验室_影像分析与机器视觉 |
| 通讯作者 | Chunheng Wang |
| 作者单位 | Institute of Automation, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Xue Chen,Chunheng Wang,Baihua Xiao,et al. Learning associate appearance manifolds for cross-pose face recognition[C],2014:1907-1911. |
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| Learning associate a（305KB） | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 | ||
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