Master Thesis - Department of Computer Science

Table 3.5: Peak Recognition Accuracy (PRA) and EER of subband face representa-
tion integrated with PCA, LDA, 2D-PCA, 2D-LDA and DCV with subject-specific
subbands obtained using four criteria on ORL database.
Subband Face(C1) Subband Face(C2) Subband Face(C3) Subband Face(C4)
Methods PRA EER PRA EER PRA EER PRA EER
PCA 88.33 4.83 88.33 4.64 88.33 4.64 81.67 7.50
LDA 88.33 4.16 87.50 4.12 87.50 4.12 89.17 4.16
2D-PCA 81.67 7.50 81.67 7.50 81.67 7.50 81.67 7.50
2D-LDA 91.67 1.67 91.67 1.81 91.67 2.50 90.00 1.98
DCV 85.83 3.44 86.67 3.50 87.50 3.33 88.33 3.59
distance metrics namely, the L1 norm, the L2 norm and the normalized correlation
coefficient. In two separate sets of experiments they searched for the subbands insen-
sitive to expression and illumination. They report that very less number of subbands
(A1, A2, A3) hold expression invariant information. The same comment does not hold
for illumination invariation. In both cases, all such subbands performing equally good
or better (compared to original face) were selected for further processing using data,
feature and decision level fusion. In decision fusion they used sum, product and max
rules.
We have experimented their technique using PCA, in two different ways. In the
first case, we follow their implementation of selecting successful subbands based on
the results obtained on testing set. This is however not technically sound in the sense
that, selected successful subbands are over-tuned on the testing set and will obviously
produce the best possible result only on the testing set. So the right way of selecting
successful subbands is to evaluate them on a validation set (as given in Section 3.4.2)
and then combine them to verify the performance on the testing set of a database.
This is the second approach used for comparing the performance of our proposed
approach with that of [36].
For the first case, Table 3.6 shows the best performing (successful) subbands
selected using the testing set. Table 3.7 shows the performance of Ekenel’s multireso-
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