Recursive Estimation of Motion, Structure, and Focal Length

Ali Azarbayejani and Alex Pentland

To appear: IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995.

We present a formulation for recursive recovery of motion, pointwise structure, and focal length from feature correspondences tracked through an image sequence. In addition to adding focal length to the state vector, several representational improvements are made over earlier structure from motion formulations, yielding a stable and accurate estimation framework which applies uniformly to both true perspective and orthographic projection. Results on synthetic and real imagery illustrate the performance of the estimator.