Hidden Factor Analysis for Age Invariant Face Recognition
文献类型：会议论文
| 作者 | Gong Dihong; Li Zhifeng; Lin Dahua; Liu Jianzhuang; Tang Xiaoou |
| 出版日期 | 2013 |
| 会议名称 | 2013 14th IEEE International Conference on Computer Vision, ICCV 2013 |
| 会议地点 | Sydney, NSW, Australia |
| 英文摘要 | Age invariant face recognition has received increasing attention due to its great potential in real world applications. In spite of the great progress in face recognition techniques, reliably recognizing faces across ages remains a difficult task. The facial appearance of a person changes substantially over time, resulting in significant intra-class variations. Hence, the key to tackle this problem is to separate the variation caused by aging from the person-specific features that are stable. Specifically, we propose a new method, called Hidden Factor Analysis (HFA). This method captures the intuition above through a probabilistic model with two latent factors: an identity factor that is age-invariant and an age factor affected by the aging process. Then, the observed appearance can be modeled as a combination of the components generated based on these factors. We also develop a learning algorithm that jointly estimates the latent factors and the model parameters using an EM procedure. Extensive experiments on two well-known public domain face aging datasets: MORPH (the largest public face aging database) and FGNET, clearly show that the proposed method achieves notable improvement over state-of-the-art algorithms. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/4494]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2013 |
| 推荐引用方式 GB/T 7714 | Gong Dihong,Li Zhifeng,Lin Dahua,et al. Hidden Factor Analysis for Age Invariant Face Recognition[C]. 见:2013 14th IEEE International Conference on Computer Vision, ICCV 2013. Sydney, NSW, Australia. |
入库方式： OAI收割
来源：深圳先进技术研究院
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