Motion and structure estimation from stereo image sequences

A closed-form approximate matrix-weighted solution for estimating motion parameters from point correspondences in two stereo image pairs is presented. The corresponding algorithm is noniterative and fast. Simulation shows that the solution is significantly more reliable than the unweighted and the s...

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Veröffentlicht in:	IEEE transactions on robotics and automation Jg. 8; H. 3; S. 362 - 382
Hauptverfasser:	Weng, J., Cohen, P., Rebibo, N.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.06.1992 Institute of Electrical and Electronics Engineers
Schlagworte:	Applied sciences Closed-form solution Computer science; control theory; systems Control theory. Systems Exact sciences and technology Filtering Gaussian noise Image sequences Iterative algorithms Kalman filters Least squares approximation Least squares methods Motion estimation Robotics Stereo vision Parameter estimation Experimental result Minimal variance Simulation Least squares method Image sequence Kalman filter Nonlinearity Closed form equation Optimal estimation Robotics Cramer Rao inequality
ISSN:	1042-296X
Online-Zugang:	Volltext
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