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ICARCV
2008
IEEE
222views Robotics» more  ICARCV 2008»
14 years 1 months ago
Robust fusion using boosting and transduction for component-based face recognition
—Face recognition performance depends upon the input variability as encountered during biometric data capture including occlusion and disguise. The challenge met in this paper is...
Fayin Li, Harry Wechsler, Massimo Tistarelli
NIPS
2001
13 years 8 months ago
Categorization by Learning and Combining Object Parts
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
ICB
2009
Springer
412views Biometrics» more  ICB 2009»
14 years 2 months ago
Bayesian Face Recognition Based on Markov Random Field Modeling
In this paper, a Bayesian method for face recognition is proposed based on Markov Random Fields (MRF) modeling. Constraints on image features as well as contextual relationships be...
Rui Wang, Zhen Lei, Meng Ao, Stan Z. Li
ECCV
2010
Springer
13 years 12 months ago
Kernel Sparse Representation for Image Classification and Face Recognition
Recent research has shown the effectiveness of using sparse coding(Sc) to solve many computer vision problems. Motivated by the fact that kernel trick can capture the nonlinear sim...
ICB
2009
Springer
251views Biometrics» more  ICB 2009»
14 years 2 months ago
Heterogeneous Face Recognition from Local Structures of Normalized Appearance
Abstract. Heterogeneous face images come from different lighting conditions or different imaging devices, such as visible light (VIS) and near infrared (NIR) based. Because heter...
ShengCai Liao, Dong Yi, Zhen Lei, Rui Qin, Stan Z....