Gait recognition using sampled point vectors

Sungjun Hong, Heesung Lee, Kyongsae Oh, Mignon Park, Euntail Kim

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

6 Citations (Scopus)

Abstract

Gait is a new biometric aimed to recognize individuals by the way they walk. Gait recognition has recently an increasing interest from researchers due to several advantages. In this paper, we have proposed a new feature vector, sampled point vector, for gait recognition based on model-free method. We choose the mean and variance of value of pixels which are sampled along to central axis of silhouette image for several frames. In contract to other system, proposed features are very simple and require low storages. Nevertheless, experimental result show sufficiently good performance. To evaluate, we use a reduced multivariate model as a classifier.

Original languageEnglish
Title of host publication2006 SICE-ICASE International Joint Conference
Pages3937-3940
Number of pages4
DOIs
Publication statusPublished - 2006
Event2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of
Duration: 2006 Oct 182006 Oct 21

Publication series

Name2006 SICE-ICASE International Joint Conference

Other

Other2006 SICE-ICASE International Joint Conference
CountryKorea, Republic of
CityBusan
Period06/10/1806/10/21

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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