CVT Project

Sparse Bundle Adjustment

Bundle Adjustmentz (BA) is almost invariably used as the last step of every feature-based multiple view reconstruction vision algorithm to obtain optimal 3D structure and motion (i.e. camera matrix) parameter estimates. Its name refers to the bundles of light rays originating from each 3D feature and converging on each camera's optical center, which are adjusted optimally with respect to both the structure and viewing parameters (similarity in meaning to categorical bundle seems a pure coincidence). 
Provided with initial estimates, BA simultaneously refines motion and structure by minimizing the reprojection error between the observed and predicted image points. The minimization is typically carried out with the aid of the Levenberg-Marquardt (LM) algorithm. 

Software

• sba: A Generic Sparse Bundle Adjustment C/C++ Package Based on the Levenberg–Marquardt Algorithm (C, Matlab)
• ssba: Simple Sparse Bundle Adjustment package based on the Levenberg–Marquardt Algorithm (C) with LGPL license.
• OpenCv: Computer Vision library in the contrib module.
• mcba: Multi-Core Bundle Adjustment (CPU/GPU).
• ROS:  ROS (Robot Operating System) provides libraries and tools to help software developers create robot applications.