Partial Face Recognition: Alignment-Free Approach
文献类型：期刊论文
| 作者 | Liao, Shengcai1,2 ; Jain, Anil K.3; Li, Stan Z.1,2
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| 刊名 | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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| 出版日期 | 2013-05-01 |
| 卷号 | 35期号:5页码:1193-1205 |
| 关键词 | Partial face recognition alignment free keypoint descriptor sparse representation open-set identification |
| 英文摘要 | Numerous methods have been developed for holistic face recognition with impressive performance. However, few studies have tackled how to recognize an arbitrary patch of a face image. Partial faces frequently appear in unconstrained scenarios, with images captured by surveillance cameras or handheld devices (e.g., mobile phones) in particular. In this paper, we propose a general partial face recognition approach that does not require face alignment by eye coordinates or any other fiducial points. We develop an alignment-free face representation method based on Multi-Keypoint Descriptors (MKD), where the descriptor size of a face is determined by the actual content of the image. In this way, any probe face image, holistic or partial, can be sparsely represented by a large dictionary of gallery descriptors. A new keypoint descriptor called Gabor Ternary Pattern (GTP) is also developed for robust and discriminative face recognition. Experimental results are reported on four public domain face databases (FRGCv2.0, AR, LFW, and PubFig) under both the open-set identification and verification scenarios. Comparisons with two leading commercial face recognition SDKs (PittPatt and FaceVACS) and two baseline algorithms (PCA+LDA and LBP) show that the proposed method, overall, is superior in recognizing both holistic and partial faces without requiring alignment. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | PARTIAL OCCLUSION ; ROBUST ; SELECTION ; MODELS ; SCALE ; REPRESENTATION ; FEATURES ; SPARSE ; IMAGES |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000316126800013 |
| 公开日期 | 2015-09-22 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/7948]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_生物识别与安全技术研究中心 |
| 作者单位 | 1.Chinese Acad Sci, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Ctr Biometr & Secur Res, Inst Automat, Beijing 100190, Peoples R China 3.Michigan State Univ, Dept Comp Sci & Engn, E Lansing, MI 48824 USA |
| 推荐引用方式 GB/T 7714 | Liao, Shengcai,Jain, Anil K.,Li, Stan Z.. Partial Face Recognition: Alignment-Free Approach[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2013,35(5):1193-1205. |
| APA | Liao, Shengcai,Jain, Anil K.,&Li, Stan Z..(2013).Partial Face Recognition: Alignment-Free Approach.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,35(5),1193-1205. |
| MLA | Liao, Shengcai,et al."Partial Face Recognition: Alignment-Free Approach".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 35.5(2013):1193-1205. |
入库方式： OAI收割
来源：自动化研究所
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