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Brunelli, R. & T. Poggio (1993), Face Recognition: Features versus Templates, IEEE Transactions on PAMI, 15(10):1042-1052.

  AUTHOR = {R. Brunelli and T. Poggio},
  TITLE = {HyperBF Networks for Real Object Reccognition},
  YEAR = 1991,
  BOOKTITLE = {Proc. of the 12th IJCAI},
  ADDRESS = "Sidney, Australia",
  PAGES = {1278-1284},
  KEYWORDS = {}}

Author of the summary: Jim Davies and Alexander Stoytchev, 2000, {jimmyd, saho}@cc.gatech.edu

Cite this paper for:

The actual paper is online in postscript format.


This paper compares two different (new) algorithms for face recognition. The first approach is based on extracting vectors of geometrical featuers and using these features for recognition. The second approach is based on template matching.

The results show that the second approach (template matching) performs better for the database of faces that was used (these results should be applied to a larger database.) It is also simpler.

As a general conclusion the authors suggest that successful face recognition systems should use a combination of the two.

Detailed Outline:

The face DataBase used consisted of 47 people (26 male and 21 female) with 4 images per person. Total 188 images (512x512 pixels). Only frontal view images were taken with constant illumination.

Feature-based approach: Find the distances and sizes of features in the face (eyes, distance to nose, etc.) and match on those feature properties.

Template approach: Match data to templates, stored as images themselves (an array of pixels with values)

Feature approach:

Template approach:

Summary author's notes:

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Last modified: Tue Feb 29 10:30:27 EST 2000