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  • Research Article
  • Open Access

Gait Recognition Using Image Self-Similarity

EURASIP Journal on Advances in Signal Processing20042004:721765

  • Received: 30 October 2002
  • Published:


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

Identix Corporation, One Exchange Place, Jersey City, NJ 07302, USA
Microsoft Research, One Microsoft Way, Redmond, WA 98052-6399, USA
Department of Computer Science, University of Maryland, College Park, MD 20742, USA


© BenAbdelkader et al. 2004