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FGR
2006
IEEE
147views Biometrics» more  FGR 2006»
14 years 1 months ago
Learning Sparse Features in Granular Space for Multi-View Face Detection
In this paper, a novel sparse feature set is introduced into the Adaboost learning framework for multi-view face detection (MVFD), and a learning algorithm based on heuristic sear...
Chang Huang, Haizhou Ai, Yuan Li, Shihong Lao
ICIP
2005
IEEE
14 years 9 months ago
Fusion of multiple viewpoint information towards 3D face robust orientation detection
This paper presents a novel approach to the problem of determining head pose estimation and face 3D orientation of several people in low resolution sequences from multiple calibra...
Cristian Canton-Ferrer, Josep R. Casas, Montse Par...
CORR
2008
Springer
159views Education» more  CORR 2008»
13 years 7 months ago
Face Detection Using Adaboosted SVM-Based Component Classifier
: Boosting is a general method for improving the accuracy of any given learning algorithm. In this paper we employ combination of Adaboost with Support Vector Machine (SVM) as comp...
Seyyed Majid Valiollahzadeh, Abolghasem Sayadiyan,...
ICCV
2005
IEEE
14 years 9 months ago
Vector Boosting for Rotation Invariant Multi-View Face Detection
In this paper, we propose a novel tree-structured multi-view face detector (MVFD), which adopts the coarse-to-fine strategy to divide the entire face space into smaller and smalle...
Chang Huang, Haizhou Ai, Yuan Li, Shihong Lao
ESANN
2004
13 years 9 months ago
Towards a Local Separation Performances Estimator Using Common ICA Contrast Functions?
Abstract. In most ICA algorithms, the separation performances are estimated through the evaluation of a contrast function , used in the update rule of elements of the unmixing matr...
Frédéric Vrins, Cédric Archam...