| | This Article | |
| |
| |
| | Share | |
| |
| |
| | Bibliographic References | |
| |
| |
| | Add to: | |
| |
 Digg
 Furl
 Spurl
 Blink
 Simpy
 Google
 Del.icio.us
 Y!MyWeb
| |
| | Search | |
| |
| |
| | |
On the Estimation of Rigid Body Rotation from Noisy Data
December 1995 (vol. 17 no. 12)
pp. 1219-1220
Abstract—We derive an exact solution to the problem of estimating the rotation of a rigid body from noisy 3D image data. Our approach is based on total least squares (TLS), but unlike previous work involving TLS, we include the constraint that the transformation matrix should be orthonormal. It turns out that the solution to the estimation problem has the same form as if the data are not noisy, and thus the solution to the standard Procrustes problem can be applied.
[1] 1219 K.S. Arun, T.S. Huang, and S.D. Blostein, "Least Squares Fitting of Two 3-(D) Point Sets," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, pp. 698-700, 1987.[2] S. Umeyama, "Least-Squares Estimation of Transformation Parameters Between Two Point Patterns," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, no. 4, pp. 376-380, Apr. 1991.[3] O.D. Faugeras and M. Hebert,“A 3D recognition and positioning algorithm using geometric primitive durfaces,” Proc. Int’l Joint Conf. Artificial Intelligence, pp. 996-1,002, Aug. 1983.[4] T.S. Huang,S.D. Blostein,, and E.A. Margerum,“Least squares estimation of motion parameters from 3D point correspondences,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 1986.[5] Golub and C.F.V. Loan, Matrix Computations.Baltimore, Md.: Johns Hopkins Univ. Press, 1989.
Index Terms:
Computer vision, rotation estimation, total least squares.
Citation:
Daniel Goryn, Søren Hein, "On the Estimation of Rigid Body Rotation from Noisy Data," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, no. 12, pp. 1219-1220, Dec. 1995, doi:10.1109/34.476514
