April 10, 2006, 3:40 p.m. PSA 113
Dept. Math. & Comp. Sci., Colorado State University
A Surprising Application of a 25 Pixel Camera
Geometric ideas for the classification of large high-dimensional data sets will
be presented and in particular the challenging problem of face recognition under
variations in illumination will be explored. It appears that the manner in which
faces reflect light under varying illumination is highly discriminatory. As a
result we are led to consider the idea of multi-set to multi-set image recognition.
These image sets may then be mapped to points on Grassman manifolds and
compared using metrics that arise naturally in this setting. We have shown that
this approach leads to error free classification on the illumination problem on
the (relatively small) CMU PIE data base. Furthermore, we show that these
results persist when we (mathematically) employ a 25 pixel camera! This work is
a collaborative effort between researchers in Mathematics and Computer Science at
Colorado State University.
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