A method for detecting dynamic objects in a visually sensed scene of a driver assistance system of a vehicle or robot with ego-motion, comprising the steps of: - providing visual signals of an environment by a vision sensor delivering dense 3D world coordinate data, said vision sensor being attached to the vehicle or robot with ego-motion, - detecting proper motion of dynamic objects on an input field of the vision sensor based on a detected optical flow, characterized by the steps of - detecting the motion of dynamic objects by using a 3D warping on the basis of predicted and sensed dense 3D world coordinate data, the predicted dense 3D world coordinate data being generated based on measured dense 3D world coordinate data, data representing the ego-motion and a region based post-processing and modeling within a 3D voxel cloud, and - combining the 3D warping-based and the optical flow based object motion detection, - wherein the 3D warping based object motion detection parameterizes, as to the direction and amplitude, the optical flow based object motion detection as to the regions indicating lateral motion of objects relative to the ego-motion, and - wherein only the regions in the 3D warping based object motion detection which indicate a lateral motion relative to the ego-motion are processed selectively by the optical flow based object motion detection, and - storing information on the detected dynamic objects and their measured motion parameters. - providing visual signals of an environment by a vision sensor delivering dense 3D world coordinate data, said vision sensor being attached to the vehicle or robot with ego-motion, - detecting proper motion of dynamic objects on an input field of the vision sensor based on a detected optical flow, characterized by the steps of - detecting the motion of dynamic objects by using a 3D warping on the basis of predicted and sensed dense 3D world coordinate data, the predicted dense 3D world coordinate data being generated based on measured dense 3D world coordinate data, data representing the ego-motion and a region based post-processing and modeling within a 3D voxel cloud, and - combining the 3D warping-based and the optical flow based object motion detection, - wherein the 3D warping based object motion detection parameterizes, as to the direction and amplitude, the optical flow based object motion detection as to the regions indicating lateral motion of objects relative to the ego-motion, and - wherein only the regions in the 3D warping based object motion detection which indicate a lateral motion relative to the ego-motion are processed selectively by the optical flow based object motion detection, and - wherein the 3D warping based object motion detection parameterizes, as to the direction and amplitude, the optical flow based object motion detection as to the regions indicating lateral motion of objects relative to the ego-motion, and - wherein only the regions in the 3D warping based object motion detection which indicate a lateral motion relative to the ego-motion are processed selectively by the optical flow based object motion detection, and - storing information on the detected dynamic objects and their measured motion parameters.