中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 09年以前成果
Learning effective intrinsic features to boost 3D-based face recognition

文献类型：期刊论文

作者Xu, Chenghua; Tan, Tieniu; Li, Stan; Wang, Yunhong; Zhong, Cheng; Leonardis, A; Bischof, H; Pinz, A
刊名COMPUTER VISION - ECCV 2006, PT 2, PROCEEDINGS
出版日期2006
卷号3952页码:416-427
英文摘要3D image data provide several advantages than 2D data for face recognition and overcome many problems with 2D intensity images based methods. In this paper, we propose a novel approach to 3D-based face recognition. First, a novel representation, called intrinsic features, is presented to encode local 3D shapes. It describes complementary nonrelational features to provide an intrinsic representation of faces. This representation is extracted after alignment, and is invariant to translation, rotation and scale. Without reduction, tens of thousands of intrinsic features can be produced for a face, but not all of them are useful and equally important. Therefore, in the second part of the work, we introduce a learning method for learning most effective local features and combining them into a strong classifier using an AdaBoost learning procedure. Experimental results are performed on a large 3D face database obtained with complex illumination, pose and expression variations. The results demonstrate that the proposed approach produces consistently better results than existing methods.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods
研究领域[WOS]Computer Science
关键词[WOS]MODEL
收录类别ISTP ; SCI
语种英语
WOS记录号WOS:000237555200032
公开日期2015-12-24
源URL[http://ir.ia.ac.cn/handle/173211/9379]  
专题自动化研究所_09年以前成果
作者单位1.Chinese Acad Sci, Inst Automat, CBSR, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Automat, NLPR, Beijing, Peoples R China
3.Beihang Univ, Sch Comp Sci & Engn, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Xu, Chenghua,Tan, Tieniu,Li, Stan,et al. Learning effective intrinsic features to boost 3D-based face recognition[J]. COMPUTER VISION - ECCV 2006, PT 2, PROCEEDINGS,2006,3952:416-427.
APA Xu, Chenghua.,Tan, Tieniu.,Li, Stan.,Wang, Yunhong.,Zhong, Cheng.,...&Pinz, A.(2006).Learning effective intrinsic features to boost 3D-based face recognition.COMPUTER VISION - ECCV 2006, PT 2, PROCEEDINGS,3952,416-427.
MLA Xu, Chenghua,et al."Learning effective intrinsic features to boost 3D-based face recognition".COMPUTER VISION - ECCV 2006, PT 2, PROCEEDINGS 3952(2006):416-427.

入库方式： OAI收割

来源：自动化研究所

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。