A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
SIAM Journal on Scientific Computing
A Supernodal Approach to Sparse Partial Pivoting
SIAM Journal on Matrix Analysis and Applications
A Fully Asynchronous Multifrontal Solver Using Distributed Dynamic Scheduling
SIAM Journal on Matrix Analysis and Applications
Bundle Adjustment - A Modern Synthesis
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
The design and implementation of a new out-of-core sparse cholesky factorization method
ACM Transactions on Mathematical Software (TOMS)
MA57---a code for the solution of sparse symmetric definite and indefinite systems
ACM Transactions on Mathematical Software (TOMS)
Algorithm 832: UMFPACK V4.3---an unsymmetric-pattern multifrontal method
ACM Transactions on Mathematical Software (TOMS)
Solving unsymmetric sparse systems of linear equations with PARDISO
Future Generation Computer Systems - Special issue: Selected numerical algorithms
Algorithm 837: AMD, an approximate minimum degree ordering algorithm
ACM Transactions on Mathematical Software (TOMS)
Algorithm 849: A concise sparse Cholesky factorization package
ACM Transactions on Mathematical Software (TOMS)
Pan-tilt-zoom camera calibration and high-resolution mosaic generation
Computer Vision and Image Understanding - Special issue on omnidirectional vision and camera networks
Direct Methods for Sparse Linear Systems (Fundamentals of Algorithms 2)
Direct Methods for Sparse Linear Systems (Fundamentals of Algorithms 2)
ACM Transactions on Mathematical Software (TOMS)
Algorithm 887: CHOLMOD, Supernodal Sparse Cholesky Factorization and Update/Downdate
ACM Transactions on Mathematical Software (TOMS)
SBA: A software package for generic sparse bundle adjustment
ACM Transactions on Mathematical Software (TOMS)
Two-view underwater structure and motion for cameras under flat refractive interfaces
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Exploring high-level plane primitives for indoor 3d reconstruction with a hand-held RGB-D camera
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Robust multi-hypothesis 3D object pose tracking
ICVS'13 Proceedings of the 9th international conference on Computer Vision Systems
Multi-view dense 3D modelling of untextured objects from a moving projector-cameras system
Machine Vision and Applications
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Several estimation problems in vision involve the minimization of cumulative geometric error using non-linear least-squares fitting. Typically, this error is characterized by the lack of interdependence among certain subgroups of the parameters to be estimated, which leads to minimization problems possessing a sparse structure. Taking advantage of this sparseness during minimization is known to achieve enormous computational savings. Nevertheless, since the underlying sparsity pattern is problem-dependent, its exploitation for a particular estimation problem requires non-trivial implementation effort, which often discourages its pursuance in practice. Based on recent developments in sparse linear solvers, this paper provides an overview of sparseLM, a generalpurpose software package for sparse non-linear least squares that can exhibit arbitrary sparseness and presents results from its application to important sparse estimation problems in geometric vision.