Journal
PATTERN RECOGNITION
Volume 46, Issue 6, Pages 1691-1699Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2012.11.022
Keywords
Face recognition; Illumination-insensitive; Illumination preprocessing; Comparative study; Holistic approach; Localized approach; Band integration
Funding
- National Basic Research Program of China (973 Program) [2009CB320902]
- Natural Science Foundation of China [61025010, 61222211]
- Beijing Natural Science Foundation (New Technologies and Methods in Intelligent Video Surveillance for Public Security) [4111003]
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Illumination preprocessing is an effective and efficient approach in handling lighting variations for face recognition. Despite much attention to face illumination preprocessing, there is seldom systemic comparative study on existing approaches that presents fascinating insights and conclusions in how to design better illumination preprocessing methods. To fill this vacancy, we provide a comparative study of 12 representative illumination preprocessing methods (HE, LT, GIC, DGD, LoG, SSR, GHP, SQL LDCT, LTV, LN and IT) from two novel perspectives: (1) localization for holistic approach and (2) integration of large-scale and small-scale feature bands. Experiments on public face databases (YaleBExt, CMU-PIE, CAS-PEAL and FRGC V2.0) with illumination variations suggest that localization for holistic illumination preprocessing methods (HE, GIC, LTV and TT) further improves the performance. Integration of large-scale and small-scale feature bands for reflectance field estimation based illumination preprocessing approaches (SSR, GHP, SQL LDCT, LTV and TT) is also found helpful for illumination-insensitive face recognition. (C) 2012 Elsevier Ltd. All rights reserved.
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