Invariant Gait Continuum Based on the Duty-Factor

In this paper we present a method to describe the continuum of human gait in an invariant manner. The gait description is based on the duty-factor which is adopted from the biomechanics literature. We generate a database of artificial silhouettes representing the three main types of gait, i.e. walking, jogging, and running. By generating silhouettes from different camera angles we make the method invariant to camera viewpoint and to changing directions of movement. Silhouettes are extracted using the Code-book method and represented in a scale- and translation-invariant manner by using shape contexts and tangent orientations. Input silhouettes are matched to the database using the Hungarian method. We define a classifier based on the dissimilarity between the input silhouettes and the gait actions of the database. This classification achieves an overall recognition rate of 87.1% on a diverse test set, which is better than that achieved by other approaches applied to similar data. We extend this classification and results show that our representation of the gait continuum preserves the main features of the duty-factor.