Yehuda Naveli, Michal Rimon, et al.
AAAI/IAAI 2006
This paper deals with robust registration of object views in the presence of uncertainties and noise in depth data. Errors in registration of multiple views of a 3D object severely affect view integration during automatic construction of object models. We derive a minimum variance estimator (MVE) for computing the view transformation parameters accurately from range data of two views of a 3D object. The results of our experiments show that view transformation estimates obtained using MVE are significantly more accurate than those computed with an unweighted error criterion for registration. ©1997 IEEE.
Yehuda Naveli, Michal Rimon, et al.
AAAI/IAAI 2006
John R. Kender, Rick Kjeldsen
IEEE Transactions on Pattern Analysis and Machine Intelligence
David W. Jacobs, Daphna Weinshall, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Anil K. Jain, Karthik Nandakumar, et al.
Pattern Recognition Letters