Skip to content

Advertisement

Open Access

Recognition of Faces in Unconstrained Environments: A Comparative Study

  • Javier Ruiz-del-Solar1Email author,
  • Rodrigo Verschae1 and
  • Mauricio Correa1
EURASIP Journal on Advances in Signal Processing20092009:184617

https://doi.org/10.1155/2009/184617

Received: 10 October 2008

Accepted: 13 March 2009

Published: 26 April 2009

Abstract

The aim of this work is to carry out a comparative study of face recognition methods that are suitable to work in unconstrained environments. The analyzed methods are selected by considering their performance in former comparative studies, in addition to be real-time, to require just one image per person, and to be fully online. In the study two local-matching methods, histograms of LBP features and Gabor Jet descriptors, one holistic method, generalized PCA, and two image-matching methods, SIFT-based and ERCF-based, are analyzed. The methods are compared using the FERET, LFW, UCHFaceHRI, and FRGC databases, which allows evaluating them in real-world conditions that include variations in scale, pose, lighting, focus, resolution, facial expression, accessories, makeup, occlusions, background and photographic quality. Main conclusions of this study are: there is a large dependence of the methods on the amount of face and background information that is included in the face's images, and the performance of all methods decreases largely with outdoor-illumination. The analyzed methods are robust to inaccurate alignment, face occlusions, and variations in expressions, to a large degree. LBP-based methods are an excellent election if we need real-time operation as well as high recognition rates.

Keywords

Facial ExpressionFace RecognitionRecognition RateHigh Recognition RateLarge Dependence

Publisher note

To access the full article, please see PDF.

Authors’ Affiliations

(1)
Department of Electrical Engineering, Universidad de Chile, Santiago, Chile

Copyright

© Javier Ruiz-del-Solar et al. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement