Visualization and Intelligent Systems Laboratory
VISLab

 

 

Contact Information

VISLab
Winston Chung Hall Room 216
University of California, Riverside
900 University Avenue
Riverside, CA 92521-0425


Tel: (951)-827-3954

CRIS
Bourns College of Engineering
UCR
NSF IGERT on Video Bioinformatics

UCR Collaborators:
CSE
ECE
ME
STAT
PSYC
ENTM
BIOL
BPSC
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Other Collaborators:
Keio University

Other Activities:
IEEE Biometrics Workshop 2014
IEEE Biometrics Workshop 2013
Worshop on DVSN 2009
Multibiometrics Book

Webmaster Contact Information:
Alex Shin
wshin@ece.ucr.edu

Last updated: July 1, 2017

 

 

Individual Recognition by Kinematic-based Gait Analysis

Presented by: Ju Han

Abstract: Current gait recognition approaches only consider individuals walking frontoparallel to the image plane. This makes them inapplicable for recognizing individuals walking from different angles with respect to the image plane. In this report, we propose a kinematic-based approach to recognize individuals by gait. The proposed approach estimates 3D human walking parameters by performing a least squares fit of the 3D kinematic model to the 2D silhouette extracted from a monocular image sequence. A Genetic algorithm is used for feature selection from the estimated parameters, and the individuals are then recognized from the feature vectors using a nearest neighbor method. Experimental results show that the proposed approach achieves good performance in recognizing individuals walking from different angles with respect to the image plane.