Title :
A new structure-from-motion ambiguity
Author_Institution :
NEC Res. Inst., Princeton, NJ, USA
Abstract :
This paper demonstrates the existence of a generic approximate ambiguity in Euclidean structure from motion (SFM) which applies to scenes with large depth variation. In projective SFM the ambiguity is absent, but the maximum-likelihood reconstruction is more likely to have occasional very large errors. The analysis gives a semi-quantitative characterization of the least-squares error surface over a domain complementary to that analyzed by Jepson/Heeger/Maybank
Keywords :
computational geometry; least squares approximations; maximum likelihood estimation; motion estimation; Euclidean structure from motion; generic approximate ambiguity; least-squares error surface; maximum-likelihood reconstruction; semi-quantitative characterization; structure-from-motion ambiguity; Cameras; Concrete; Costs; Error analysis; Image analysis; Image motion analysis; Image reconstruction; Layout; National electric code; Surface reconstruction;
Conference_Titel :
Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on.
Conference_Location :
Fort Collins, CO
Print_ISBN :
0-7695-0149-4
DOI :
10.1109/CVPR.1999.786937