Discriminative filtering with principal component analysis and adaptive alignment

Discriminative filtering is a pattern recognition technique which seeks to maximize the energy of output signal when a pattern is found. To improve the robustness, was incorporated the principal component analysis in discriminative filters design. In this work, we proposed a new technique for design of the discriminative filters, called adaptive alignment. To evaluation, we used a facial fiducial points detection system with BioID database.