| | |
Summary: Is Levenberg-Marquardt the Most Efficient Optimization Algorithm for
Implementing Bundle Adjustment?
Manolis I.A. Lourakis and Antonis A. Argyros
Institute of Computer Science, Foundation for Research and Technology - Hellas
Vassilika Vouton, P.O. Box 1385, GR 711 10, Heraklion, Crete, GREECE”
lourakis, argyros¢ @ics.forth.gr
Abstract
In order to obtain optimal 3D structure and viewing pa-
rameter estimates, bundle adjustment is often used as the
last step of feature-based structure and motion estimation
algorithms. Bundle adjustment involves the formulation of
a large scale, yet sparse minimization problem, which is tra-
ditionally solved using a sparse variant of the Levenberg-
Marquardt optimization algorithm that avoids storing and
operating on zero entries. This paper argues that consid-
erable computational benefits can be gained by substitut-
ing the sparse Levenberg-Marquardt algorithm in the im-
plementation of bundle adjustment with a sparse variant of
Powell's dog leg non-linear least squares technique. De-
|
