Paper Available: Face Recognition using Spatial Filters and

[rao@cs.rochester.edu]

Sparse Distributed Memory


The following paper is currently available via ftp:

Rajesh P. N. Rao and Dana H. Ballard, "Natural Basis Functions and
Topographic Memory for Face Recognition", IJCAI'95 (to appear).

ftp://cs.rochester.edu/pub/u/rao/papers/ijcai95.ps.Z

Abstract:

  Recent work regarding the statistics of natural images has revealed
  that the dominant eigenvectors of arbitrary natural images closely
  approximate various oriented derivative-of-Gaussian functions; these
  functions have also been shown to provide the best fit to the
  receptive field profiles of cells in the primate striate cortex. We
  propose a scheme for expression-invariant face recognition that
  employs a fixed set of these ``natural'' basis functions to generate
  multiscale iconic representations of human faces. Using a fixed set
  of basis functions obviates the need for recomputing eigenvectors (a
  step that was necessary in some previous approaches employing
  principal component analysis (PCA) for recognition) while at the
  same time retaining the redundancy-reducing properties of PCA.  A
  face is represented by a set of iconic representations automatically
  extracted from an input image. The description thus obtained is
  stored in a topographically-organized sparse distributed memory that
  is based on a model of human long-term memory first proposed by
  Kanerva. We describe experimental results for an implementation of
  the method on a pipeline image processor that is capable of
  achieving near real-time recognition by exploiting the processor's
  frame-rate convolution capability for indexing purposes.


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Rajesh Rao                       Internet: rao at cs.rochester.edu
Dept. of Computer Science        VOX:  (716) 275-2527              
University of Rochester          FAX:  (716) 461-2018
Rochester  NY  14627-0226        WWW:  http://www.cs.rochester.edu/u/rao/