2 new TRs: face recognition, shape similarity

[Edelman Shimon]

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URL: 	ftp://eris.wisdom.weizmann.ac.il/pub/maria-tr.ps.Z

Maria Lando and Shimon Edelman

Generalization from a single view in face recognition

  We describe a computational model of face recognition, which
  generalizes from single views of faces by taking advantage of prior
  experience with other faces, seen under a wider range of viewing
  conditions. The model represents face images by vectors of
  activities of graded overlapping receptive fields (RFs). It relies
  on high spatial frequency information to estimate the viewing
  conditions, which are then used to normalize (via a transformation
  specific for faces), and identify, the low spatial frequency
  representation of the input. The class-specific transformation
  approach allows the model to replicate a series of psychophysical
  findings on face recognition, and constitutes an advance over
  current face recognition methods, which are incapable of
  generalization from a single example.

22 pages; uncompressed Postscript file size: 3563304 bytes (600dpi)
(a shorter, 6-page version is also available, as maria-short.ps.Z)
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URL: 	ftp://eris.wisdom.weizmann.ac.il/pub/cs-tr-95-01.ps.Z

Florin Cutzu and Shimon Edelman 

Explorations of shape space

  Using a small number of prototypical reference objects to span the
  internal shape representation space has been suggested as a general
  approach to the problem of object representation in vision (Edelman,
  Minds and Machines 5, 1995, in press).  We have investigated the
  ability of human subjects to form the low-dimensional metric shape 
  representation space predicted by this approach. In each of a series of
  experiments, which involved pairwise similarity judgment, and
  delayed match to sample, subjects were confronted with several
  classes of computer-rendered 3D animal-like shapes, arranged in a
  complex pattern in a common high-dimensional parameter space.  We
  combined response time and error rate data into a measure of view
  similarity, and submitted the resulting proximity matrix to
  nonmetric multidimensional scaling (MDS). In the two-dimensional MDS
  solution, views of the same shape were invariably clustered
  together, and, in each experiment, the relative geometrical
  arrangement of the view clusters of the different objects reflected
  the true low-dimensional structure in parameter space (star,
  triangle, square, line) that defined the relationships between the
  stimuli classes. These findings are now used used to guide the
  development of a detailed computational theory of shape vision based
  on similarity to prototypes.

33 pages; uncompressed Postscript file size: 3887463 bytes (600dpi)
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Related papers available at URL 

	http://www.wisdom.weizmann.ac.il/~edelman/archive.html

Comments are welcome.

-Shimon

Shimon Edelman      E-MAIL: edelman at wisdom.weizmann.ac.il    TEL: +972-8-342856
FAX: +972-8-344122  WWW: http://eris.wisdom.weizmann.ac.il/~edelman/shimon.html
Dept. of Appl. Math. & CS, Weizmann Institute of Science, Rehovot 76100, ISRAEL