Multi-View Nonparametric Discriminant Analysis for Image Retrieval and Recognition

Abstract

A novel multi-view nonparametric discriminant analysis method is proposed for the application of cross-modal image retrieval and zero-shot recognition. We exploit the class boundary structure and discrepancy information of the available views in order to formulate an optimization criterion which is automatically adjusted to the multi-view class structures. The proposed method allows for multiple projection directions, by relaxing the Gaussian distribution assumption of related methods. The experiments demonstrate that the proposed method can achieve superior results comparing to several existing methods.