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MVA
2007
309views Computer Vision» more  MVA 2007»
13 years 9 months ago
Robust Facial Feature Extraction Using Embedded Hidden Markov Model for Face Recognition under Large Pose Variation
We propose an algorithm for extracting facial features robustly from images for face recognition under large pose variation. Rectangular facial features are retrieved via the by-p...
Ping-Han Lee, Yun-Wen Wang, Jison Hsu, Ming-Hsuan ...
PAMI
2012
12 years 7 days ago
A Blur-Robust Descriptor with Applications to Face Recognition
—Understanding the effect of blur is an important problem in unconstrained visual analysis. We address this problem in the context of image-based recognition, by a fusion of imag...
Raghuraman Gopalan, Sima Taheri, Pavan K. Turaga, ...
ICCV
2001
IEEE
14 years 11 months ago
Lambertian Reflectance and Linear Subspaces
We prove that the set of all Lambertian reflectance functions (the mapping from surface normals to intensities) obtained with arbitrary distant light sources lies close to a 9D lin...
Ronen Basri, David W. Jacobs
ACCV
2009
Springer
14 years 4 months ago
Image-Set Based Face Recognition Using Boosted Global and Local Principal Angles
Face recognition using image-set or video sequence as input tends to be more robust since image-set or video sequence provides much more information than single snapshot about the ...
Xi Li, Kazuhiro Fukui, Nanning Zheng
CVPR
2004
IEEE
14 years 11 months ago
How Features of the Human Face Affect Recognition: A Statistical Comparison of Three Face Recognition Algorithms
Recognition difficulty is statistically linked to ??? subject covariate factors such as age and gender for three face recognition algorithms: principle components analysis, an int...
Geof H. Givens, J. Ross Beveridge, Bruce A. Draper...