Tracking of persons in monocular image sequences

We present an approach to extract quantitative geometric descriptions of the movements of persons by fitting the projection of a 3-dimensional human model to consecutive frames of an image sequence. The kinematics of the human model is given by a homogeneous transformation tree and its body parts are modeled by right-elliptical cones. The proposed approach can determine the values of a varying number of degrees of freedom (DOFs; body joints, position and orientation of the person relative to the camera) according to the application and the kind of image sequence. The determination of the DOFs is understood as an estimation problem which is solved by an iterated extended Kalman filter (IEKF). For this purpose, the human model is augmented by a simple motion model of constant velocity for all DOFs which is used in the prediction step of the IEKF. In the update step both region and edge information is used.