sba : A Generic Sparse Bundle Adjustment C/C++ Package Based on the Levenberg-Marquardt Algorithm This site concerns sba, a C/C++ package for generic sparse bundle adjustment that is distributed under the GNU General Public License (GPL). Bundle Adjustment (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. 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. However, due to the large number of unknowns contributing to the minimized reprojection error, a general purpose implementation of the LM algorithm (such as MINPACK’s lmder) incurs high computational costs when applied to the minimization problem defined in the context of BA. Fortunately, the lack of interaction among parameters for different 3D points and cameras results in the underlying normal equations exhibiting a sparse block structure (click here for an example). sba exploits this sparseness by employing a tailored sparse variant of the LM algorithm that leads to considerable computational gains. sba is generic in the sense that it grants the user full control over the definition of the parameters describing cameras and 3D structure. Therefore, it can support virtually any manifestation/parameterization of the multiple view reconstruction problem such as arbitrary projective cameras, partially or fully intrinsically calibrated cameras, exterior orientation (i.e. pose) estimation from fixed 3D points, refinement of intrinsic parameters, etc. All the user has to do to adapt sba to any such problem is to supply it with appropriate routines for computing the estimated image projections and their Jacobian for the problem and parameterization at hand. Routines for computing analytic Jacobians can be either coded by hand, generated with a tool supporting symbolic differentiation (e.g. maple), or obtained using automatic differentiation techniques. There is also the alternative of approximating Jacobians with the aid of finite differences. Additionally, sba includes routines for checking the consistency of user-supplied Jacobians. To the best of our knowledge, sba is the first and currently the only software package of its kind to be released as free software. (Source:

References in zbMATH (referenced in 24 articles )

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  1. Terzakis, George; Lourakis, Manolis; Ait-Boudaoud, Djamel: Modified Rodrigues parameters: an efficient representation of orientation in 3D vision and graphics (2018)
  2. Özyeşil, Onur; Voroninski, Vladislav; Basri, Ronen; Singer, Amit: A survey of structure from motion (2017)
  3. Gaspar, Tiago; Oliveira, Paulo; Favaro, Paolo: Synchronization of independently moving cameras via motion recovery (2016)
  4. Hollósi, Gergely; Lukovszki, Csaba; Moldován, István; Plósz, Sándor; Harasztos, Frigyes: Monocular indoor localization techniques for smartphones (2016)
  5. Martínez, Pablo A.; Castelán, Mario; Arechavaleta, Gustavo: Vision based persistent localization of a humanoid robot for locomotion tasks (2016)
  6. Aftab, Khurrum; Hartley, Richard; Trumpf, Jochen: (L_q)-closest-point to affine subspaces using the generalized Weiszfeld algorithm (2015)
  7. Park, Hyun Soo; Shiratori, Takaaki; Matthews, Iain; Sheikh, Yaser: 3D trajectory reconstruction under perspective projection (2015)
  8. Ceylan, Duygu; Mitra, Niloy J.; Zheng, Youyi; Pauly, Mark: Coupled structure-from-motion and 3D symmetry detection for urban facades (2014)
  9. Mou, Wei; Wang, Han; Seet, Gerald: Robust homography estimation based on nonlinear least squares optimization (2014)
  10. Diaz, Mauricio; Sturm, Peter: Estimating photometric properties from image collections (2013)
  11. Bajramovic, Ferid; Brückner, Marcel; Denzler, Joachim: An efficient shortest triangle paths algorithm applied to multi-camera self-calibration (2012)
  12. Lin, Wen-Yan; Cheong, Loong-Fah; Tan, Ping; Dong, Guo; Liu, Siying: Simultaneous camera pose and correspondence estimation with motion coherence (2012)
  13. Liu, Xin; Gao, Wei; Hu, Zhan-Yi: Hybrid parallel bundle adjustment for 3D scene reconstruction with massive points (2012)
  14. Solà, Joan; Vidal-Calleja, Teresa; Civera, Javier; Montiel, José María Martínez: Impact of landmark parametrization on monocular EKF-SLAM with points and lines (2012)
  15. Franceschini, Fiorenzo; Galetto, Maurizio; Maisano, Domenico; Mastrogiacomo, Luca; Pralio, Barbara: Distributed large-scale dimensional metrology. New insights (2011)
  16. Torii, Akihiko; Havlena, Michal; Pajdla, Tomáš: Omnidirectional image stabilization for visual object recognition (2011)
  17. Kim, Jae-Hean; Chung, Myung Jin; Choi, Byung Tae: Recursive estimation of motion and a scene model with a two-camera system of divergent view (2010)
  18. Furukawa, Yasutaka; Ponce, Jean: Accurate camera calibration from multi-view stereo and bundle adjustment (2009) ioport
  19. Lourakis, Manolis I. A.; Argyros, Antonis A.: SBA: a software package for generic sparse bundle adjustment (2009)
  20. Nicosevici, Tudor; Gracias, Nuno; Negahdaripour, Shahriar; Garcia, Rafael: Efficient three-dimensional scene modeling and mosaicing (2009)

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