A methodology for improving recognition rate of linear discriminant analysis in video-based face recognition using support vector machines

Sreekar Krishna, Sethuraman Panchanathan

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

3 Scopus citations

Abstract

This paper proposes a two-step methodology for improving the discriminatory power of Linear Discriminant Analysis (LDA) for video-based human face recognition. Results indicate that, under real-world video capture conditions, face images extracted from a video sequence have enough 3D rotations, illumination changes and background variations to reduce the discriminatory power of an LDA classifier. The proposed method involves deriving an LDA subspace from carefully selected subsets of face images that fall within a narrow range of pose angles, and then growing the classification regions in the LDA subspace using face images with a wider range of pose angle changes, illumination changes, and background variations. Polynomial Support Vector Machines (SVM) are shown to provide better recognition rates by defining the boundaries between clusters that represent the faces of different subjects. Results show that there is an improvement in the recognition rate when the LDA subspace is derived with this methodology than when it is derived with a set of face images with a widely divergent set pose angles, illumination variations, and backgrounds.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Multimedia and Expo, ICME 2005
Pages1054-1057
Number of pages4
DOIs
StatePublished - Dec 1 2005
EventIEEE International Conference on Multimedia and Expo, ICME 2005 - Amsterdam, Netherlands
Duration: Jul 6 2005Jul 8 2005

Publication series

NameIEEE International Conference on Multimedia and Expo, ICME 2005
Volume2005

Other

OtherIEEE International Conference on Multimedia and Expo, ICME 2005
CountryNetherlands
CityAmsterdam
Period7/6/057/8/05

ASJC Scopus subject areas

  • Engineering(all)

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    Krishna, S., & Panchanathan, S. (2005). A methodology for improving recognition rate of linear discriminant analysis in video-based face recognition using support vector machines. In IEEE International Conference on Multimedia and Expo, ICME 2005 (pp. 1054-1057). [1521606] (IEEE International Conference on Multimedia and Expo, ICME 2005; Vol. 2005). https://doi.org/10.1109/ICME.2005.1521606