Least-Squares Estimation of Transformation Parameters Between Two Point Patterns

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 13, Issue 4, 1991, Pages 376-380

  Umeyama, Shinji ^a  

^a ELECTROTECHNICAL LABORATORY   (Japan)

Author keywords

Absolute orientation problem; computer vision; least squares; motion estimation; singular value decomposition

Indexed keywords

MATHEMATICAL TECHNIQUES - LEAST SQUARES APPROXIMATIONS;

IMAGE ORIENTATION; LEAST SQUARES ESTIMATION; MACHINE VISION; PATTERN TRANSFORMATIONS; POINT PATTERNS; SIMILARITY TRANSFORMATIONS;

COMPUTER VISION;

EID: 0026137964     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/34.88573     Document Type: Article

References (7)

1. B. K. P. Horn, “Closed-form solution of absolute orientation using or-thonormal matrices,” J. Opt. Soc. Amer. A, vol. 5, no. 7, pp. 1127–1135, 1987.
2. T. S. Huang, S. D. Blostein, and E. A. Margerum, “Least-squares estimation of motion parameters from 3-D point correspondences,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition, Miami Beach, FL, 1986, pp. 24–26.
3. B. K. P. Horn, “Closed-form solution of absolute orientation using unit quaternions,” J. Opt. Soc. Amer. A, vol. 4, no. 4, pp. 629–642, 1987.
4. K. S. Arun, T. S. Huang, and S. D. Blostein, “Least-squares fitting of two 3-D point sets,” IEEE Trans. Pattern Anal. Machine Intell, vol. PAMI-9, no. 5, pp. 698–700, 1987.
5. M. Athans, “The matrix minimum principle,” Inform. Contr., vol. 11, pp. 592–606, 1967.
6. R. Bellman, Introduction to Matrix Analysis. New York: McGraw-Hill, 1960, p. 56.
7. D. Holder and H. Buxton, “AVC89: Polyhedral object recognition with sparse data—Validation of interpretations,” in Proc. Fifth Alvey Vision Conf, 1989, pp. 19–24.