Motion estimation with incomplete information using omni-directional vision

We present a new motion estimation framework and apply it to omni-directional imagery. Our method estimates motions incrementally using an implicit extended Kalman filter (IEKF). Each individual feature provides partial information about the camera motion. The motion estimate is incrementally improved as each feature is processed, similar to the SCAAT approach. The SCAAT method was developed for calibrated features and full 6DOF-pose tracking whereas our method estimates 5DOF translation and rotation motions concurrently from uncalibrated features based on the rigidity and the depth independent constraints. The main difference of our method from others is the combination of a recursive estimation framework in an IEKF and the constraints used in motion estimation.