Recognition of Faces in Unconstrained Environments: A Comparative Study

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ID: 12356
2009
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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.
Reference Key
ruizdelsolar2009recognitioneurasip Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ruiz-del-Solar, Javier;Verschae, Rodrigo;Correa, Mauricio;
Journal eurasip journal on advances in signal processing
Year 2009
DOI
DOI not found
URL
http://dx.doi.org/10.1155/2009/184617
Keywords Keywords not found

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