AUTOMATIC GAIT RECOGNITION
Abstract

Gait is an emergent biometric aimed essentially to recognise people by the way they walk. Gaitâ„¢s advantages are that it requires no contact, like automatic face recognition, and that it is less likely to be obscured than other biometrics. Gait has allied subjects including medical studies, psychology, human body modelling and motion tracking. These lend support to the view that gait has clear potential as a biometric. Essentially, we use computer vision techniques to derive a gait signature from a sequence of images. The majority of current approaches analyse an image sequence to derive motion characteristics that are then used for recognition; only one approach is feature based. Early results by these studies confirm that there is a rich potential in gait for recognition. Only continued development will confirm whether its performance can equal that of other biometrics and whether its application advantages will indeed make it a pragmatistâ„¢s choice.

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Presented By:
M.S. Nixon, J.N. Carter,
D. Cunado, P.S. Huang, S.V. Stevenage
University of Southampton
Southampton, UK

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Introduction

In many applications of person identification, many established biometrics can be obscured. The face may be hidden or at low resolution; the palm is obscured; the ears cannot be seen. However, people need to walk, so their gait is usually apparent. This motivates using gait as a biometric and it has recently attracted interest. Gait is attractive since it requires no subject contact, in common with automatic face recognition and other biometrics. The Oxford Dictionary definition of gait is manner of walking, bearing or carriage as one walks suggesting that studies can concentrate on different facets of a personâ„¢s walk. Apart from perceptibility, another attraction of using gait is that motion can be hard to disguise. Consider for example a robbery: the robber will need to make access either quickly, to minimize likelihood of capture, or Nixon et al. without being obvious in order not to provoke attention. On escape, again the robber will either exit at speed, or in (apparent) leisure. The motion in both cases is natural, for the subject will either not want to attract attention or to move quickly. Clearly, there are limits to the use of gait as a biometric, a detailed study of the limitations awaits development of technique. However, it is not unlikely that footwear can affect gait, as can clothing. Equally, physical condition can affect gait such as pregnancy, affliction of the legs or feet, or even drunkenness. These factors are not new to biometrics: a face can be made up or have spectacles, ears can be obscured by hair, hands can even be cut off, as acknowledged in other chapters. As usual, a major question concerns whether these are part of human perception whereas a biometric system can perceive the underlying characteristics of the biometric - in the case of gait, the individualâ„¢s musculature which essentially limits the variation of motion. As such, these factors await investigation. The view that gait can be used to recognize individual is not new: Shakespeare used a rich lexicon of adjectives to describe gait, including princely, lionâ„¢s, heavy, humble, weary, forced, gentle, swimming, and majestic. Further, in The Tempest [Act 4 Scene 1], Ceres observes Highâ„¢st Queen of state, Great Juno comes; I know her by her gait. Even more, in Troilius and Cressida Ulysses states Tis he, I ken the manner of his gait; He rises on the toe: that spirit of his in aspiration lifts him from the earth. The former is one of Shakespeareâ„¢s many observations on recognizing people by their gait; the latter includes a concise description of Diomedesâ„¢ demeanour. Accordingly, there appears much potential for using gait as a biometric. There have been allied studies, particularly those in medical studies for therapy, but there have also been psychological studies, and approaches aimed to model and track human targets through an image sequence, though not usually for recognition, as discussed in Section 2. Current approaches to automatic gait recognition are surveyed in Section 3, together with a more detailed examination of two extant approaches to automatic recognition. Possibilities for further work are discussed in Section 4 prior to the conclusions concerning the potential for gait as a biometric.

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