Analysis of Noteworthy Issues in Illumination Processing for Face Recognition

Min YAO  Hiroshi NAGAHASHI  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E98-D   No.3   pp.681-691
Publication Date: 2015/03/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2014EDP7112
Type of Manuscript: PAPER
Category: Image Recognition, Computer Vision
Keyword: 
face recognition,  illumination processing,  noteworthy issues,  analysis,  evaluation,  

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Summary: 
Face recognition under variable illumination conditions is a challenging task. Numbers of approaches have been developed for solving the illumination problem. In this paper, we summarize and analyze some noteworthy issues in illumination processing for face recognition by reviewing various representative approaches. These issues include a principle that associates various approaches with a commonly used reflectance model and the shared considerations like contribution of basic processing methods, processing domain, feature scale, and a common problem. We also address a more essential question-what to actually normalize. Through the discussion on these issues, we also provide suggestions on potential directions for future research. In addition, we conduct evaluation experiments on 1) contribution of fundamental illumination correction to illumination insensitive face recognition and 2) comparative performance of various approaches. Experimental results show that the approaches with fundamental illumination correction methods are more insensitive to extreme illumination than without them. Tan and Triggs' method (TT) using L1 norm achieves the best results among nine tested approaches.