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Human gait characteristics from unconstrained walks and viewpoints

We propose a new method for view-invariant gait modeling using a single calibrated camera. Piecewise-continuous body parts trajectories extracted from a video sequence are rectified to appear as observed from a fronto-parallel view. Standard gait characteristics are then computed by combining rectified gait half-cycles from each trajectory. In this method, we make use of a walk model that allows changes in direction as well as changes in speed in order to decouple gait characteristics from distracting factors in the observed sequence. In contrast with previous work, our method is thus well suited for both clinical and surveillance applications. Simulated and real trajectories from an indoor setting are used to validate the proposed method.