Open Access

Gait Recognition Using Image Self-Similarity

EURASIP Journal on Advances in Signal Processing20042004:721765

https://doi.org/10.1155/S1110865704309236

Received: 30 October 2002

Published: 21 April 2004

Abstract

Gait is one of the few biometrics that can be measured at a distance, and is hence useful for passive surveillance as well as biometric applications. Gait recognition research is still at its infancy, however, and we have yet to solve the fundamental issue of finding gait features which at once have sufficient discrimination power and can be extracted robustly and accurately from low-resolution video. This paper describes a novel gait recognition technique based on the image self-similarity of a walking person. We contend that the similarity plot encodes a projection of gait dynamics. It is also correspondence-free, robust to segmentation noise, and works well with low-resolution video. The method is tested on multiple data sets of varying sizes and degrees of difficulty. Performance is best for fronto-parallel viewpoints, whereby a recognition rate of 98% is achieved for a data set of 6 people, and 70% for a data set of 54 people.

Keywords and phrases

gait recognition human identification at a distance human movement analysis behavioral biometrics pattern recognition

Authors’ Affiliations

(1)
Identix Corporation, One Exchange Place
(2)
Microsoft Research, One Microsoft Way
(3)
Department of Computer Science, University of Maryland

Copyright

© BenAbdelkader et al. 2004