Recognition of Faces in Unconstrained Environments: A Comparative Study

EURASIP Journal on Advances in Signal Processing. 2009;2009 DOI 10.1155/2009/184617

 

Journal Homepage

Journal Title: EURASIP Journal on Advances in Signal Processing

ISSN: 1687-6172 (Print); 1687-6180 (Online)

Publisher: Springer

Society/Institution: European Association for Signal Processing (EURASIP)

LCC Subject Category: Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication | Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics

Country of publisher: United Kingdom

Language of fulltext: English

Full-text formats available: PDF, HTML

 

AUTHORS

Javier Ruiz-del-Solar
Rodrigo Verschae
Mauricio Correa

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 13 weeks

 

Abstract | Full Text

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.