Rhythmic Gait Signature from Video without Motion Capture

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Sadikali, Akil
Boyd, Jeffrey
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Abstract
The goal of gait biometrics is usually to identify individual people from a distance, often without their knowledge. As such, gait biometrics provide a source of data that ties a visible pattern of motion to an individual. We describe our work to convert one particular biometric gait signature into a rhythmic sound pattern that is unique for different individuals. We begin with a camera viewing a person walking on a treadmill, then extract a phase configuration that describes the timing pattern of motions in the gait. The timing pattern is then converted to a rhythmic percussion pattern that allows one to hear differences and similarities across a population of gaits. We can also hear phase patterns in a gait independent of the actual frequency of the gait. Our approach avoids the inconvenience and cost of traditional motion capture methods. We demonstrate our system with the sonification of 25 gaits from the CMU Motion of Body database
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2010-06
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