Illumination Modeling for Face Recognition


In this chapter, we show that effective systems can account for the effects of lighting using fewer than 10 degrees of freedom. This can have considerable impact on the speed and accuracy of recognition systems. We will describe theoretical results that, with some simplifying assumptions, prove the validity of low-dimensional, linear approximations to the set of images produced by a face.


Face Recognition Linear Subspace Query Image Harmonic Image Cast Shadow 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Major portions of this research were conducted while Ronen Basri and David Jacobs were at the NEC Research Institute, Princeton, NJ. At the Weizmann Institute Ronen Basri is supported in part by European Community grants IST-2000-26001 VIBES and IST-2002-506766 Aim Shape and by the Israel Science Foundation grant 266/02. The vision group at the Weizmann Institute is supported in part by the Moross Foundation. David Jacobs was funded by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), through the Army Research Laboratory (ARL). All statements of fact, opinion or conclusions contained herein are those of the authors and should not be construed as representing the official views or policies of IARPA, the ODNI, or the U.S. Government.


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.The Weizmann Institute of ScienceRehovotIsrael
  2. 2.University of MarylandCollege ParkUSA

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