Abstract
In this thesis, we introduce a real time two orthogonal views human motion analysis system. We use two cameras to capture the facade and flank views of the human motion. To track the motion of the human object, we propose two methods to estimate the motion parameters (BAPs) of the human arm and leg. First, we use Kalman filter to predict arms posture. Second, we track the leg by model-based matching method. The human motion analysis is divided into macro motion analysis and micro motion analysis. The former identifies the certain well-defined postures and the latter traces the variation of joint angle parameters. Before tracking, we analyze the vertical projection profile and horizontal projection profile in each view to identify postures. With the identified postures, we can apply the Kalman filter to track the motion of joint angels and generate the BAPs.