Comparing and combining lighting insensitive approaches for face recognition

TitleComparing and combining lighting insensitive approaches for face recognition
Publication TypeJournal Articles
Year of Publication2010
AuthorsGopalan R, Jacobs DW
JournalComputer Vision and Image Understanding
Pagination135 - 145
Date Published2010/01//
ISBN Number1077-3142
KeywordsClassifier comparison and combination, face recognition, Gradient direction, lighting

Face recognition under changing lighting conditions is a challenging problem in computer vision. In this paper, we analyze the relative strengths of different lighting insensitive representations, and propose efficient classifier combination schemes that result in better recognition rates. We consider two experimental settings, wherein we study the performance of different algorithms with (and without) prior information on the different illumination conditions present in the scene. In both settings, we focus on the problem of having just one exemplar per person in the gallery. Based on these observations, we design algorithms for integrating the individual classifiers to capture the significant aspects of each representation. We then illustrate the performance improvement obtained through our classifier combination algorithms on the illumination subset of the PIE dataset, and on the extended Yale-B dataset. Throughout, we consider galleries with both homogenous and heterogeneous lighting conditions.