1.School of Information Science and Technology,University of Science and Technology of China,Hefei 230026 2.Research Centre for Information Technology of Sports and Health,Institute of Intelligent Machines,Chinese Academy of Sciences,Hefei 230031
Abstract A gait recognition method based on spatio-temporal histogram of oriented gradient (HOG) is proposed. Spatio-temporal HOG embodies the feature fusion of spatial and temporal plantar pressure information. Firstly,several key points,such as the maximum and the minimum points on the pressure-time curve,are picked out. Then,plantar pressure distribution images corresponding to the moment of key points are used to construct spatio-temporal HOG feature vector. Finally,support vector machine classification is applied to implement gait classification. Gait samples are collected from 30 persons at different walking speeds. When the walking speeds of the samples in the training and testing sets are not differentiated,the recognition rate is 93.5%. The experimental results demonstrate that spatio-temporal HOG feature accurately describes the dynamic plantar pressure distribution during walking,and it also has good speed-adaptable properties.
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2013, Vol. 26 
