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Building Class Sensitive Models for Tracking Applications

A method of generating complementary eigenspaces optimised for interclass and intra-class separability respectively is presented. The objective of creating these spaces is to improve the efficiency of eigenspace search algorithms. The inter-class optimised space may also be used to improve classification and a quantitative evaluation of this against conventional Principal Component Analysis and Canonical analysis (based on Linear Discriminant Analysis) is presented. A qualitative comparison of the intra-class optimised space and spaces produced by Principal Component Analysis on single class data is also presented.