J4 ›› 2012, Vol. 39 ›› Issue (5): 96-101+167.doi: 10.3969/j.issn.1001-2400.2012.05.017

• Original Articles • Previous Articles     Next Articles

Classification method for multimodal data-class dependent ELDA

REN Huorong;LI Chunxiao;SUN Jianwei;QIN Hongbo;HE Peipei;GAO Min   

  1. (School of Mechano-electronic Engineering, Xidian Univ., Xi'an  710071, China)
  • Received:2011-10-24 Online:2012-10-20 Published:2012-12-13
  • Contact: REN Huorong E-mail:hrren@mail.xidian.edu.cn

Abstract:

Multimodal data refer to the data of a class that can be divided into two or more clusters. This paper proposes an improved method which is called the class-dependent and enhanced method. Enhanced LDA is combined with class-dependent LDA (CDLDA) to classify the multimodal data. In the new algorithm, we first use Enhanced LDA to reduce the dimensionality of multimodal data without losing the local structure and then get a projection matrix for each data class to obtain the characteristic differences for different data class distribution by the maximum scatter difference discriminant analysis criterion. Experiments on the face databases show the encouraging recognition performance of the proposed algorithm.

Key words: multimodal data, classification, LDA, enhanced LDA, class-dependence