• DocumentCode
    720679
  • Title

    WM-SBA: Weighted multibody sparse bundle adjustment

  • Author

    Cordes, Kai ; Hockner, Mark ; Ackermann, Hanno ; Rosenhahn, Bodo ; Ostermann, Jorn

  • Author_Institution
    Inst. fur Informationsverarbeitung (TNT), Hannover, Germany
  • fYear
    2015
  • fDate
    18-22 May 2015
  • Firstpage
    162
  • Lastpage
    165
  • Abstract
    Sparse bundle adjustment (SBA) is the state of the art method for simultaneously optimizing a set of camera poses and 3D points. The multibody bundle adjustment optimizes the static scene and the moving rigid object(s). The result is one camera path representing the main camera motion and virtual camera path(s) for each of the independently moving objects in the scene. The bundle adjustment for the multibody problem is performed in a joint optimization. Main motion (static scene) and object motion(s) are included in the optimization such that the sparse algorithm of SBA can still be applied, even when enforcing the constraint that main camera and object camera share the same intrinsic parameters. The joint optimization approach enables weighting the resulting error for each of the motion models and therefore influences the optimization process. Our experiments with synthetic and natural image data show that an appropriate weighting leads to more accurate camera parameters.
  • Keywords
    Jacobian matrices; cameras; motion estimation; object detection; optimisation; 3D points; WM-SBA; camera path; camera poses; independently moving objects; joint optimization; main camera motion; weighted multibody sparse bundle adjustment; Cameras; Jacobian matrices; Joints; Noise; Optimization; Three-dimensional displays; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision Applications (MVA), 2015 14th IAPR International Conference on
  • Conference_Location
    Tokyo
  • Type

    conf

  • DOI
    10.1109/MVA.2015.7153158
  • Filename
    7153158