LITERATURE SURVEY OF AUTOMATIC FACE RECOGNITION ...

oughly the same scale), scale normalization was used such that in the combined
data base, all images have roughly the same scale.
Table 5.2.1
The Original Data Bases and Their Variations.
Database Subject Variation Total
MIT 16 27 432
Olivetti 40 10 400
Weizmann 28 30 840
Bern 30 10 300
Table 5.2.2
The “Trimmed” Data Bases and Their Variations.
Database Subject Variation Total
MIT 16 3 48
Olivetti 40 2 80
Weizmann 28 3 84
Bern 30 2 60
Combined 114 2,3 272
The Eigenface, Auto­Association and classification nets, and elastic
matching algorithms were run on each of the four individual data bases as well
as on the combined data base. In this test first the researcher’s intention to test
these algorithms robustness over different data bases, later on they decided to
test these algorithms efficacy on a relatively large data base in terms of the
number of subjects.
In their experiments, the images were divided into training and test sets.
To describe how the training samples were picked, we first need to describe how
the data bases are organized.
The four individual data bases (MIT, Olivetti, Weizmann, and Bern) have
the same organization, and the combined data base, being the combination of
the four, also has that organization. Specifically, in each data base, every subject
is photographed under a number of settings, say, settings 1, 2, 3…., k. Here, a
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