Gait Identification Considering Body Tilt by Walking Direction Changes

Yasushi Makihara, Ryusuke Sagawa, Yasuhiro Mukaigawa, Tomio Echigo, Yasushi Yagi

Abstract

Gait identification has recently gained attention as a method of identifying individuals at a distance.
Thought most of the previous works mainly treated straight-walk sequences for simplicity, curved-walk sequences
should be also treated considering situations where a person walks along a curved path or enters a
building from a sidewalk. In such cases, person’s body sometimes tilts by centrifugal force when walking
directions change, and this body tilt considerably degrades gait silhouette and identification performance,
especially for widely-used appearance-based approaches. Therefore, we propose a method of body-tilted silhouette
correction based on centrifugal force estimation from walking trajectories. Then, gait identification
process including gait feature extraction in the frequency domain and learning of a View Transformation
Model (VTM) follows the silhouette correction. Experiments of gait identification for circular-walk sequences
demonstrate the effectiveness of the proposed method.

Keywords

Gait identification; Body tilt correction; Fourier analysis; View Transformation Model

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