Title :
An experimental study of projective structure from motion
Author :
Oliensis, John ; Govindu, Venu
Author_Institution :
NEC Res. Inst., Princeton, NJ, USA
fDate :
7/1/1999 12:00:00 AM
Abstract :
We describe an essentially algorithm-independent experimental comparison of projective versus Euclidean reconstruction. The Euclidean approach is as accurate as the projective one, even with significant calibration error and for the pure projective structure. Projective optimization has less of a local-minima problem than its Euclidean equivalent. We describe techniques that enhance the convergence of optimization algorithms
Keywords :
calibration; convergence; image motion analysis; image reconstruction; image sequences; matrix algebra; optimisation; Euclidean reconstruction; calibration error; local-minima problem; projective optimization; projective reconstruction; projective structure from motion; Calibration; Cameras; Convergence; Geometry; Image reconstruction; Layout; Nonlinear distortion; Reconstruction algorithms; Robustness; Venus;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on