Automatic detection of facial feature points via HOGs and geometric prior models

Authors:
Mario Rojas Quiñones;David Masip;Jordi Vitrià
Affiliations:
Computer Vision Center, Universitat Autònoma de Barcelona;Computer Vision Center, Universitat Autònoma de Barcelona and Universitat Oberta de Catalunya;Computer Vision Center, Universitat Autònoma de Barcelona and Dept. de Matemàtica Aplicada i Anàlisi, Universitat de Barcelona
Venue:
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Year:
2011

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Abstract

Most applications dealing with problems involving the face require a robust estimation of the facial salient points. Nevertheless, this estimation is not usually an automated preprocessing step in applications dealing with facial expression recognition. In this paper we present a simple method to detect facial salient points in the face. It is based on a prior Point Distribution Model and a robust object descriptor. The model learns the distribution of the points from the training data, as well as the amount of variation in location each point exhibits. Using this model, we reduce the search areas to look for each point. In addition, we also exploit the global consistency of the points constellation, increasing the detection accuracy. The method was tested on two separate data sets and the results, in some cases, outperform the state of the art.