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SCIA
2009
Springer
195views Image Analysis» more  SCIA 2009»
13 years 12 months ago
Multi-band Gradient Component Pattern (MGCP): A New Statistical Feature for Face Recognition
A feature extraction method using multi-frequency bands is proposed for face recognition, named as the Multi-band Gradient Component Pattern (MGCP). The MGCP captures discriminativ...
Yimo Guo, Jie Chen, Guoying Zhao, Matti Pietik&aum...
TASLP
2008
133views more  TASLP 2008»
13 years 5 months ago
Minimum Mean-Squared Error Estimation of Mel-Frequency Cepstral Coefficients Using a Novel Distortion Model
In this paper, a new method for statistical estimation of Mel-frequency cepstral coefficients (MFCCs) in noisy speech signals is proposed. Previous research has shown that model-ba...
Kevin M. Indrebo, Richard J. Povinelli, Michael T....
CVPR
2007
IEEE
14 years 9 months ago
Discriminant Mutual Subspace Learning for Indoor and Outdoor Face Recognition
Outdoor face recognition is among the most challenging problems for face recognition. In this paper, we develop a discriminant mutual subspace learning algorithm for indoor and ou...
Zhifeng Li, Dahua Lin, Helen M. Meng, Xiaoou Tang
ICPR
2010
IEEE
13 years 11 months ago
Monogenic Binary Pattern (MBP): A Novel Feature Extraction and Representation Model for Face Recognition
A novel feature extraction method, namely monogenic binary pattern (MBP), is proposed in this paper based on the theory of monogenic signal analysis, and the histogram of MBP (HMB...
Meng Yang, Lei Zhang, Lin Zhang, David Zhang
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