| Abstract |
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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.
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 Additional Information
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Citation:
David Nister,
"Preemptive RANSAC for Live Structure and Motion Estimation,"
iccv,
p. 199,
Ninth IEEE International Conference on Computer Vision (ICCV'03) - Volume 1,
2003
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