Range of motion estimation from Mocap data

In this paper, we propose a novel technique to estimate joint ROM (range of motion) from Mocap (motion capture) data. For each joint, the probability density function of joint angle is estimated by mixture of Gaussian, and the angle space is divided into Voronoi cells which have a kernel of Gaussian at these centers. Then, the sets of the Voronoi cells in two different joints, which occur in the Mocap data, are used to approximate the ROM taking into account the change related to the angle of the other joint. As all of this estimation processes are performed on the simple ball joint model, we do not need to introduce any complex musculo-skeletal model. Our method can also estimate the ROMs even for the joints which have difficulty to measure the angle directly by physical measurement as well as the joints of limbs