Parameterized discriminant analysis for image classification

Qi Tian, Jie Yu, Ting Rui, Thomas S Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years, linear and nonlinear (i.e., kernel) discriminant analysis has been proposed to address the difficulties of small sample problem, curse of dimensionality, and multi-modality of image data distribution in content-based image retrieval (CBIR). The existing discriminant analysis is implemented either in a regular way such as MDA (C=2 for FDA) or in a biased way such as biased discriminant analysis (BDA). In this paper, a rich set of parameterized discriminant analysis is proposed as an alternative of the regular MDA and BDA when taking the regularization into account to avoid the singularity of the scatter matrices. Extensive experiments are carried out for performance evaluation and the results show the superior performance of the parameterized discriminant analysis over regular MDA and BDA for both linear and nonlinear settings.

Original languageEnglish (US)
Title of host publication2004 IEEE International Conference on Multimedia and Expo (ICME)
Pages5-8
Number of pages4
StatePublished - Dec 1 2004
Event2004 IEEE International Conference on Multimedia and Expo (ICME) - Taipei, Taiwan, Province of China
Duration: Jun 27 2004Jun 30 2004

Publication series

Name2004 IEEE International Conference on Multimedia and Expo (ICME)
Volume1

Other

Other2004 IEEE International Conference on Multimedia and Expo (ICME)
CountryTaiwan, Province of China
CityTaipei
Period6/27/046/30/04

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint Dive into the research topics of 'Parameterized discriminant analysis for image classification'. Together they form a unique fingerprint.

  • Cite this

    Tian, Q., Yu, J., Rui, T., & Huang, T. S. (2004). Parameterized discriminant analysis for image classification. In 2004 IEEE International Conference on Multimedia and Expo (ICME) (pp. 5-8). (2004 IEEE International Conference on Multimedia and Expo (ICME); Vol. 1).