Abstract
When recognizing a fixed object from a fixed viewpoint, the
dominant source of variation in image intensity is lighting changes. We
propose a low-dimensional model for human faces that can both synthesize
a face image when given lighting conditions and can estimate lighting
conditions when given a face image. The model can handle non-Lambertian
and self-shadowing surfaces such as faces because it does not make any
assumptions about either the surface geometry or bidirectional
reflectance function. The model can be adapted to handle any arbitrary
lighting condition, and is easily extendable to any other viewpoint or
to any other object
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