Experiments and uniqueness results on object structure and kinematics from a sequence of monocular images

The authors consider the problem of using a sequence of monocular images (central projections) of a three-dimensional (3-D) moving object to estimate both its structure and kinematics. The object is assumed to be rigid, and its motion is assumed to be `smooth´. A set of object match points is assumed to be available, consisting of fixed features on the object, the image-plane coordinates of which have been extracted from successive images in the sequence. The measured data are the noisy image plane coordinates of this set of object match points, taken from each image in the sequence. Results of an experiment with real imagery are presented, involving estimation of 28 unknown translational, rotational, and structural parameters, based on 12 images with seven feature points. Uniqueness results are summarized for the case of purely translational motion. A test based on a singular-value decomposition is described that determines whether or not noise-free data from an image sequence uniquely determines the elements of any given parameter vector, and sample uniqueness results are given. It is concluded that the experimental and the uniqueness results presented demonstrate the feasibility of the proposed approach