DocumentCode
3082289
Title
Fast, robust, and consistent camera motion estimation
Author
Zhang, Tong ; Tomasi, Carlo
Author_Institution
Dept. of Comput. Sci., Stanford Univ., CA, USA
Volume
1
fYear
1999
fDate
1999
Abstract
Previous algorithms that recover camera motion from image velocities suffer from both bias and excessive variance in the results. We propose a robust estimator of camera motion that is statistically consistent when image noise is isotropic. Consistency means that the estimated motion converges in probability, to the true value as the number of image points increases. An algorithm based on reweighted Gauss-Newton iterations handles 100 velocity measurements in about 50 milliseconds on a workstation
Keywords
motion estimation; noise; probability; velocity measurement; camera motion; consistent camera motion estimation; image noise; image points; image velocities; reweighted Gauss-Newton iterations; robust estimator; velocity measurements; Cameras; Image converters; Least squares methods; Motion estimation; Newton method; Noise robustness; Probability; Recursive estimation; Velocity measurement; Workstations;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on.
Conference_Location
Fort Collins, CO
ISSN
1063-6919
Print_ISBN
0-7695-0149-4
Type
conf
DOI
10.1109/CVPR.1999.786934
Filename
786934
Link To Document