Matching 2.5D face scans to 3D models

The performance of face recognition systems that use two-dimensional images depends on factors such as lighting and subject's pose. We are developing a face recognition system that utilizes three-dimensional shape information to make the system more robust to arbitrary pose and lighting. For ea...

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Bibliographic Details
Published in:	IEEE transactions on pattern analysis and machine intelligence Vol. 28; no. 1; pp. 31 - 43
Main Authors:	Xiaoguang Lu, Jain, A.K., Colbry, D.
Format:	Journal Article
Language:	English
Published:	Los Alamitos, CA IEEE 01.01.2006 IEEE Computer Society The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	3D model Algorithms appearance-based Applied sciences Artificial Intelligence Biometry - methods Computer science; control theory; systems Engines Exact sciences and technology Face - anatomy & histology Face recognition Galleries Humans Illumination Image analysis Image Interpretation, Computer-Assisted - methods Image matching Imaging, Three-Dimensional - methods Independent component analysis Index Terms- Face recognition Iterative algorithms Iterative closest point algorithm Lighting Matching multimodal Pattern Recognition, Automated - methods Pattern recognition. Digital image processing. Computational geometry Photogrammetry - methods Photography - methods Reproducibility of Results Robustness Sensitivity and Specificity Shape Studies Subtraction Technique Surface matching Texture Three dimensional Image texture Discriminant analysis Face recognition Image processing Image databank 3D model multimodal Pattern recognition appearance-based surface matching Three dimensional model Facies Tridimensional image Multimodal interface Pattern analysis
ISSN:	0162-8828, 1939-3539
Online Access:	Get full text
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