%0 Conference Proceedings
%T Robust and Efficient Multipose Face Detection Using Skin Color Segmentation
%A Murad Al Haj
%A Andrew Bagdanov
%A Jordi Gonzalez
%A Xavier Roca
%B 4th Iberian Conference on Pattern Recognition and Image Analysis
%D 2009
%V 5524
%I Springer Berlin Heidelberg
%@ 0302-9743
%@ 978-3-642-02171-8
%F Murad Al Haj2009
%O ISE
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1216), last updated on Tue, 17 Dec 2013 16:04:01 +0100
%X In this paper we describe an efficient technique for detecting faces in arbitrary images and video sequences. The approach is based on segmentation of images or video frames into skin-colored blobs using a pixel-based heuristic. Scale and translation invariant features are then computed from these segmented blobs which are used to perform statistical discrimination between face and non-face classes. We train and evaluate our method on a standard, publicly available database of face images and analyze its performance over a range of statistical pattern classifiers. The generalization of our approach is illustrated by testing on an independent sequence of frames containing many faces and non-faces. These experiments indicate that our proposed approach obtains false positive rates comparable to more complex, state-of-the-art techniques, and that it generalizes better to new data. Furthermore, the use of skin blobs and invariant features requires fewer training samples since significantly fewer non-face candidate regions must be considered when compared to AdaBoost-based approaches.
%U http://dx.doi.org/10.1007/978-3-642-02172-5_21