Gait or an individuals manner of walking, is one approach for recognizing people at a distance. Studies in psychophysics and medicine indicate that humans can recognize people by their gait and have found twenty-four different components to gait that taken together make it a unique signature. Besides not requiring close sensor contact, gait also does not necessarily require a cooperative subject. Using video data of people walking in different scenarios and environmental conditions we develop and test an algorithm that uses shape and motion to identify people from their gait. The algorithm uses dynamic time warping to match stored templates against an unknown sequence of silhouettes extracted from a person walking. While results under similar constraints and conditions are very good, the algorithm quickly degrades with varying conditions such as surface and clothing.
Recognition Using Gait
2007
14 pages
Report
No indication
English
Personnel Detection , Human Factors Engineering , Biomedical Instrumentation & Bioengineering , Anatomy , Pattern Recognition & Image Processing , Walking , Computer imaging , Psychophysics , Pattern recognition , Video data , Algorithms , Shapes , Motions , Graphics , Identification , Unique signatures , Gait recognition , Dynamic time warping
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