Bibliographic record for `Lourakis:2009:SSP'

@Article{Lourakis:2009:SSP,
  author =       "Manolis I. A. Lourakis and Antonis A. Argyros",
  title =        "{SBA}: A Software Package for Generic Sparse Bundle Adjustment",
  journal =      "{ACM} Transactions on Mathematical Software",
  accepted =     "23 May 2008",
  upcoming =     "true",
  abstract =     "Bundle adjustment constitutes a large, nonlinear least-squares problem that is often solved as the last step 
                 of feature-based structure and motion estimation computer vision algorithms to obtain optimal estimates. Due
                 to the very large number of parameters involved, a general purpose least-squares algorithm incurs high 
                 computational and memory storage costs when applied to bundle adjustment. Fortunately, the lack of interaction 
                 among certain subgroups of parameters results in the corresponding Jacobian being sparse, a fact that can be 
                 exploited to achieve considerable computational savings. This paper presents {\tt sba}, a publicly available 
                 C/C++ software package for realizing generic bundle adjustment with high efficiency and flexibility regarding 
                 parameterization.",
}