Fast gait parameter estimation for frontal view gait video data based on the model selection and parameter optimization approach

We study the problem of analyzing and classifying frontal view gait video data. In this study, we focus on the human walking speed and amplitude of arm swing and leg swing, we estimate these parameters using the statistical registration and modeling on a video data. To demonstrate the effectiveness of our method, we apply our gait parameter estimation model for the human gait video data. As a result, our model is able to estimate the gait parameters by stably at low calculation cost.

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