•Minimizing g is
difficult:
–g is non-linear due to rotations, perspective
division
–lots of parameters: 3 for
each 3D point, 6 for each camera
–difficult to initialize
–gauge ambiguity: error is invariant to a similarity
transform (translation,
rotation, uniform scale)
•
•Many techniques use
non-linear least-squares (NLLS) optimization
(bundle adjustment)
–Levenberg-Marquardt is one
common algorithm for NLLS
–Lourakis, The Design and Implementation of a Generic Sparse Bundle Adjustment Software Package Based on the
Levenberg-Marquardt
Algorithm, http://www.ics.forth.gr/~lourakis/sba/
–