This paper describes a pattern classification approach for detecting frontal-view faces via learning a decision boundary. The classification can be achieved either by explicit est...
: 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...
This paper presents a method for face recognition across large changes in viewpoint. Our method is based on a Morphable Model of 3D faces that represents face-specific information...
Volker Blanz, Patrick Grother, P. Jonathon Phillip...
We present two methods using mixtures of linear subspaces for face detection in gray level images. One method uses a mixture of factor analyzers to concurrently perform clustering...
Ming-Hsuan Yang, Narendra Ahuja, David J. Kriegman
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...