Face detection with boosted Gaussian features

Authors:
Julien Meynet;Vlad Popovici;Jean-Philippe Thiran
Affiliations:
Ecole Polytechnique Fédérale de Lausanne (EPFL), Signal Processing Institute, CH-1015 Lausanne, Switzerland;Bioinformatics Core Facility, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland;Ecole Polytechnique Fédérale de Lausanne (EPFL), Signal Processing Institute, CH-1015 Lausanne, Switzerland
Venue:
Pattern Recognition
Year:
2007

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Abstract

Detecting faces in images is a key step in numerous computer vision applications, such as face recognition or facial expression analysis. Automatic face detection is a difficult task because of the large face intra-class variability which is due to the important influence of the environmental conditions on the face appearance. We propose new features based on anisotropic Gaussian filters for detecting frontal faces in complex images. The performances of our face detector based on these new features have been evaluated on reference test sets, and clearly show improvements compared to the state-of-the-art.