Complex-Matrix-Based horizontal and vertical discriminant analysis for feature fusion

Authors:
Xiuping Wang;Caikou Chen
Affiliations:
Information Engineering Department, Jiangsu Animal Husbandry & Veterinary College, Taizhou, China,Information Engineering College, Yangzhou University, Yangzhou, China;Information Engineering College, Yangzhou University, Yangzhou, China
Venue:
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
Year:
2012

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Abstract

Considering the serial strategy generally used in feature fusion easily leads to curse of dimensionality and two-dimensional matrix for image representation outperforms one-dimensional vector, a novel strategy of parallel complex-matrix-based horizontal and vertical discriminant analysis is developed in this paper. It first respectively utilizes two different images of a subject as the real and imaginary part of a complex matrix, two-step discriminant analysis, namely horizontal LDA and vertical PCA, is then performed in the complex feature space. The experimental results demonstrate that the proposed method is more promising and effective.