Combining local features for robust nose location in 3D facial data
文献类型:期刊论文
作者 | Xu, Chenghua; Tan, Tie![]() |
刊名 | PATTERN RECOGNITION LETTERS
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出版日期 | 2006-10-01 |
卷号 | 27期号:13页码:1487-1494 |
关键词 | nose tip location local surface features local statistical features included angle curve SVM |
英文摘要 | Due to the wide use of human face images, it is significant to locate facial feature points. In this paper, we focus on 3D facial data and propose a novel method to solve a specific problem, i.e., locating the nose tip by one hierarchical filtering scheme combining local features. Based on the detected nose tip, we further estimate the nose ridge by a newly defined curve, the Included Angle Curve (IAC). The key features of our method are its automated implementation for detection, its ability to deal with noisy and incomplete input data, its invariance to rotation and translation, and its adaptability to different resolutions. The experimental results from different databases show the robustness and feasibility of the proposed method. (c) 2006 Elsevier B.V. All rights reserved. |
WOS标题词 | Science & Technology ; Technology |
类目[WOS] | Computer Science, Artificial Intelligence |
研究领域[WOS] | Computer Science |
关键词[WOS] | RECOGNITION |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000239355100009 |
公开日期 | 2015-12-24 |
源URL | [http://ir.ia.ac.cn/handle/173211/9378] ![]() |
专题 | 自动化研究所_09年以前成果 |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China 2.Beihang Univ, Sch Comp Sci & Engn, Beijing 100083, Peoples R China 3.Hong Kong Univ Sci & Technol, Dept Comp Sci, Kowloon, Hong Kong, Peoples R China |
推荐引用方式 GB/T 7714 | Xu, Chenghua,Tan, Tie,Wang, Yunhong,et al. Combining local features for robust nose location in 3D facial data[J]. PATTERN RECOGNITION LETTERS,2006,27(13):1487-1494. |
APA | Xu, Chenghua,Tan, Tie,Wang, Yunhong,&Quan, Long.(2006).Combining local features for robust nose location in 3D facial data.PATTERN RECOGNITION LETTERS,27(13),1487-1494. |
MLA | Xu, Chenghua,et al."Combining local features for robust nose location in 3D facial data".PATTERN RECOGNITION LETTERS 27.13(2006):1487-1494. |
入库方式: OAI收割
来源:自动化研究所
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