Regularized eigenspace-based gait recogntion system for human identification

Byungyun Lee, Sungjun Hong, Heesung Lee, Euntai Kim

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

5 Citations (Scopus)

Abstract

Gait has received much interest from the biometric society in the vision field due to its utility in walker identification. In this paper, we present a regularized eigenspace-based gait recognition system for human identification. First, motion contour image (MCI) is extracted from walking sequences. In training phase, eigenfeature regularization and extraction (ERE) is applied to the gallery motion contour image to obtain regularized transformation matrix and gallery features. In test phase, regularized transformation matrix is applied to project motion contour image into the eigenspace to obtain probe features, and determine the identity based on the result of nearest neighbor classifier. Experiments are performed with the CASIA gait database A to evaluate the performance of the proposed gait recognition system. Experimental results justify the superiority of our proposed system in terms of correct classification rate.

Original languageEnglish
Title of host publicationProceedings of the 2011 6th IEEE Conference on Industrial Electronics and Applications, ICIEA 2011
Pages1966-1970
Number of pages5
DOIs
Publication statusPublished - 2011
Event2011 6th IEEE Conference on Industrial Electronics and Applications, ICIEA 2011 - Beijing, China
Duration: 2011 Jun 212011 Jun 23

Publication series

NameProceedings of the 2011 6th IEEE Conference on Industrial Electronics and Applications, ICIEA 2011

Other

Other2011 6th IEEE Conference on Industrial Electronics and Applications, ICIEA 2011
Country/TerritoryChina
CityBeijing
Period11/6/2111/6/23

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering

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