We study the problems of the structure model and speed parameter estimation for scales of moving object on the video data with application to gait analysis. A study on the human gait is important in the fields of the biometrics study and the sports/health managements for planning optimal trainings. The motion capture system can give the precise measurements of trajectories of moving objects, but it requires the laboratory environments and this cannot be used in the field study. On the other hand, the video camera is handy to observe the gait motion in the field study, but such data has many restrictions on analysis based on the filming conditions. In particular, the video data filmed from the frontal-view is difficult to analyze, because the subject getting closer to the camera, and observed data includes the scale-changing parameters. To cope with this, Okusa et al. (2010) proposed a registration algorithm for scales of moving object using the method of nonlinear least squares with application to the gait analysis assuming constant speed. In this article, focusing on the human gait cycles and speeds, we consider the human gait modeling based on simple gait structure. We estimate the parameters of the human gait cycles and speeds using the method of nonlinear least squares (Okusa et al., 2010). We also show that estimated parameters may be used for the human gait analysis.
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