Simultaneous estimation of 3D shape and motion of objects by computer vision

A recursive estimation method based on the 4D-approach to real-time computer vision for simultaneously determining both 3D shape parameters and motion state of objects is discussed. The recognition processes exploit structurally given shape models and motion models given by difference-equations. This allows to confine the image analysis to feature evaluation of the last frame of the sequence only; no differencing between images has to be done, yet the spatial motion components (satisfying planar motion constraints) are recovered directly without inverting the perspective projection equations of the imaging process explicitly. Object recognition has been confined to a well structured, but otherwise general dynamic scene for the beginning: road traffic with a limited class of vehicles.<<ETX>>