Face Recognition Based on LFDA and LS-SVM

Qi Shen; Ruixiang Liu

doi:10.1109/ett.2009.43

ScienceGate Book Chapters

JOURNAL ARTICLE

Face Recognition Based on LFDA and LS-SVM

Qi Shen Ruixiang Liu

Year: 2009 Vol: 8 Pages: 136-139

DOI: 10.1109/ett.2009.43

Get Full-Text PDF Get Analytical Report

Abstract

Face recognition is one of the most challenging research topics in the field of pattern recognition and computer vision. To efficiently deal with this problem, a novel face recognition algorithm is proposed by the combination of local fisher discriminant analysis (LFDA) and least square version of SVM (LS-SVM). Experimental results on real face databases have demonstrated the better performance of the proposed algorithm.

Keywords:

Facial recognition system Artificial intelligence Linear discriminant analysis Support vector machine Pattern recognition (psychology) Face (sociological concept) Computer science Field (mathematics) Discriminant Machine learning Mathematics

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.14

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Remote Sensing and Land Use

Physical Sciences → Earth and Planetary Sciences → Atmospheric Science

Advanced Algorithms and Applications

Physical Sciences → Engineering → Control and Systems Engineering

Face Recognition Based on LFDA and LS-SVM

Abstract

Metrics

Citation History

Topics

Related Documents

KPCA Based on LS-SVM for Face Recognition

Face Recognition Based on Improved LBP and LS-SVM

Face Recognition Based on Sub-image Feature Extraction and LS-SVM

Speaker Recognition Based on LS-SVM

Handwritten Digit Recognition Based on LS-SVM