Title :
Preemptive RANSAC for live structure and motion estimation
Author_Institution :
Sarnoff Corp., Princeton, NJ, USA
Abstract :
A system capable of performing robust live ego-motion estimation for perspective cameras is presented. The system is powered by random sample consensus with preemptive scoring of the motion hypotheses. A general statement of the problem of efficient preemptive scoring is given. Then a theoretical investigation of preemptive scoring under a simple inlier-outlier model is performed. A practical preemption scheme is proposed and it is shown that the preemption is powerful enough to enable robust live structure and motion estimation.
Keywords :
computer vision; motion estimation; random processes; video cameras; ego-motion estimation; inlier-outlier model; live structure; motion hypotheses; preemptive RANSAC; preemptive scoring; random sample consensus; Cameras; Collaboration; Computer vision; Cost function; Delay estimation; Government; Layout; Motion estimation; Real time systems; Robustness;
Conference_Titel :
Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on
Conference_Location :
Nice, France
Print_ISBN :
0-7695-1950-4
DOI :
10.1109/ICCV.2003.1238341
