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Biometric Gait Recognition

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Part of the Lecture Notes in Computer Science book series (LNIP,volume 3161)

Abstract

Psychological studies indicate that people have a small but statistically significant ability to recognize the gaits of individuals that they know. Recently, there has been much interest in machine vision systems that can duplicate and improve upon this human ability for application to biometric identification. While gait has several attractive properties as a biometric (it is unobtrusive and can be done with simple instrumentation), there are several confounding factors such as variations due to footwear, terrain, fatigue, injury, and passage of time. This paper gives an overview of the factors that affect both human and machine recognition of gaits, data used in gait and motion analysis, evaluation methods, existing gait and quasi gait recognition systems, and uses of gait analysis beyond biometric identification. We compare the reported recognition rates as a function of sample size for several published gait recognition systems.

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Boyd, J.E., Little, J.J. (2005). Biometric Gait Recognition. In: Tistarelli, M., Bigun, J., Grosso, E. (eds) Advanced Studies in Biometrics. Lecture Notes in Computer Science, vol 3161. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11493648_2

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  • DOI: https://doi.org/10.1007/11493648_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26204-6

  • Online ISBN: 978-3-540-28638-7

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