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Sirface vs. Fisherface: recognition using class specific linear projection

10 years 1 months ago
Sirface vs. Fisherface: recognition using class specific linear projection
Using a novel data dimension reduction method proposed in statistics, we develop an appearance-based face recognition algorithm which is insensitive to large variation in lighting direction and facial expression. Taking a pattern classification approach, we consider each pixel in an image as coordinate in a highdimensional space. However, since faces are not truly Lambertian surfaces and indeed produce self-shadowing, images will deviate from this linear subspace. Rather than explicitly modeling this deviation, we linearly project the image into a subspace in a manner which discounts those regions of the face with large deviation using Sliced Inverse Regression (SIR) [9]. Our face recognition algorithm termed as Sirface produces well-separated classes in a low-dimensional subspace, even under severe variation in lighting and facial expression. Sirface can be shown to be equivalent to the well known Fisherface algorithm [1] in the subspace sense. However, Sirface is shown to produce th...
Yangrong Ling, Xiangrong Yin, Suchendra M. Bhandar
Added 24 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2003
Where ICIP
Authors Yangrong Ling, Xiangrong Yin, Suchendra M. Bhandarkar
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