CASIA OpenIR  > 09年以前成果
Learning effective intrinsic features to boost 3D-based face recognition
Xu, Chenghua; Tan, Tieniu; Li, Stan; Wang, Yunhong; Zhong, Cheng; Leonardis, A; Bischof, H; Pinz, A
Source PublicationCOMPUTER VISION - ECCV 2006, PT 2, PROCEEDINGS
2006
Volume3952Pages:416-427
SubtypeArticle
Abstract3D 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 HeadingsScience & Technology ; Technology
WOS KeywordMODEL
Indexed ByISTP ; SCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:000237555200032
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9379
Collection09年以前成果
Affiliation1.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
Recommended Citation
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.
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