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ICCV
2001
IEEE
15 years 3 days ago
Learning Inhomogeneous Gibbs Model of Faces by Minimax Entropy
In this paper we propose a novel inhomogeneous Gibbs model by the minimax entropy principle, and apply it to face modeling. The maximum entropy principle generalizes the statistic...
Ce Liu, Song Chun Zhu, Heung-Yeung Shum
ICPR
2004
IEEE
14 years 11 months ago
Real-Time Face Detection Using Boosting in Hierarchical Feature Spaces
Boosting-basedmethods have recently led to the state-ofthe-art face detection systems. In these systems, weak classifiers to be boosted are based on simple, local, Haar-like featu...
Daniel Gatica-Perez, Dong Zhang, Stan Z. Li
ICIAP
2007
ACM
14 years 10 months ago
Generalization in Holistic versus Analytic Processing of Faces
The distinction between holistic and analytical (or feature-based) approaches to face recognition is widely held to be an important dimension of face recognition research. Holisti...
Manuele Bicego, Albert Ali Salah, Enrico Grosso, M...
ICCV
2007
IEEE
14 years 4 months ago
Hierarchical Ensemble of Global and Local Classifiers for Face Recognition
In the literature of psychophysics and neurophysiology, many studies have shown that both global and local features are crucial for face representation and recognition. This paper...
Yu Su, Shiguang Shan, Xilin Chen, Wen Gao
WACV
2007
IEEE
14 years 4 months ago
Probabilistic Hierarchical Face Model for Feature Localization
Facial feature localization is an important research area in both computer vision and pattern analysis. We present in this paper a hierarchical face model. It unifies both the gl...
Feng Tang, Jin Wang, Hai Tao, Qunsheng Peng