A Maximum Entropy Feature Descriptor for Age Invariant Face Recognition
文献类型：会议论文
| 作者 | Dihong Gong; Zhifeng Li; Dacheng Tao; Jianzhuang Liu; Xuelong Li |
| 出版日期 | 2015 |
| 会议名称 | IEEE Conference on Computer Vision and Pattern Recognition |
| 会议地点 | 美国波士顿 |
| 英文摘要 | In this paper, we propose a new approach to overcome the representation and matching problems in age invariant face recognition. First, a new maximum entropy feature descriptor (MEFD) is developed that encodes the microstructure of facial images into a set of discrete codes in terms of maximum entropy. By densely sampling the encoded face image, sufficient discriminatory and expressive information can be extracted for further analysis. A new matching method is also developed, called identity factor analysis (IFA), to estimate the probability that two faces have the same underlying identity. The effectiveness of the framework is confirmed by extensive experimentation on two face aging datasets, MORPH (the largest public-domain face aging dataset) and FGNET. We also conduct experiments on the famous LFW dataset to demonstrate the excellent generalizability of our new approach. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/6695]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2015 |
| 推荐引用方式 GB/T 7714 | Dihong Gong,Zhifeng Li,Dacheng Tao,et al. A Maximum Entropy Feature Descriptor for Age Invariant Face Recognition[C]. 见:IEEE Conference on Computer Vision and Pattern Recognition. 美国波士顿. |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。