**Tseng and Sood 1989
:** An approach for
analyzing image sequences for motion parameter estimation is presented. A
sequence of an arbitrary number of image frames is utilized to determine
rotational and translational parameters. A dynamic scene model is developed in
which image sequences are processed as a temporally correlated complex. The
object motion is represented as a discrete-time time-varying system. The
measurement consists of a sequence of image coordinates of three or more
feature points in each frame. Using this model, measurement of the position of
the object in a set of consecutive frames permits the estimation of motion as a
function of time. An iterative parameter estimation technique is used to
minimize the projection error. The technique is based on results from optimal
control theory. Motion parameters are estimated from the sequences of image
correspondences by modeling the motion dynamics using motion transformation and
viewing projection. This methodology is suitable for processing a long sequence
in situations where a high rate of imagery is available. Results are presented
for general rigid-body motion in the context of synthesized images and real
robot images.