A Weighted Combination of Classifiers Employing Shared and Distinct Representations

Authors:
J. Kittler;S. A. Hojjatoleslami
Affiliations:
-;-
Venue:
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Year:
1998

Citing 3
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Abstract

This paper presents a theoretical framework for the combination of soft decisions generated by experts employing mixed (some shared and some distinct) object representations. By taking the confidence of the individual experts into account, weighted benevolent fusion strategies are derived. This provides a basis for combining classifiers and illustrates that a substantial gain in performance can be achieved by fusing the opinions of multiple experts. These strategies are experimentally tested and their effectiveness is considered.