Model-Based 3D Motion Analysis via Robust Estimation

Within a human motion analysis system, body parts are modeled by simple virtual 3D rigid objects. Its position and orientation parameters a t frame t+ 1 are estimated based on the parameters a t frame t and the image intensity variation from frame t to t + 1, under kinematic constraints. An optimization procedure calculates the 3D parameters that make a goal function that measures the intensity change minimum. The goal function is robust, so that outliers located especially near the virtual object projection borders have less effect on the estimation. Since the object's parameters are relative to the reference system, they are the same from different cameras, so more cameras are easily added, increasing the constraints over the same number of variables. A successful experiment is presented for an arm motion of three parts seen from two cameras.