Self-Calibration from Optical Flow and Its Reliability Evaluation

Abstract An algorithm is presented for 3-D reconstruction from optical flow observed by an uncalibrated camera. We show that by incorporating a statistical model of image noise, we can not only compute a statistically optimal shape but also evaluate its reliability in quantitative terms. We show real-image experiments and discuss the effect of the "gauge" on the uncertainty description