中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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; Wang, Yunhong; Quan, Long
刊名PATTERN RECOGNITION LETTERS
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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