Probabilistic object tracking using a range camera

@article{Wthrich2013ProbabilisticOT,
  title={Probabilistic object tracking using a range camera},
  author={Manuel W{\"u}thrich and P. Pastor and Mrinal Kalakrishnan and Jeannette Bohg and S. Schaal},
  journal={2013 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year={2013},
  pages={3195-3202}
}
  • Manuel Wüthrich, P. Pastor, +2 authors S. Schaal
  • Published 2013
  • Computer Science
  • 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
  • We address the problem of tracking the 6-DoF pose of an object while it is being manipulated by a human or a robot. We use a dynamic Bayesian network to perform inference and compute a posterior distribution over the current object pose. Depending on whether a robot or a human manipulates the object, we employ a process model with or without knowledge of control inputs. Observations are obtained from a range camera. As opposed to previous object tracking methods, we explicitly model self… CONTINUE READING
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    References

    SHOWING 1-10 OF 22 REFERENCES
    Combined shape, appearance and silhouette for simultaneous manipulator and object tracking
    • 43
    Robotic Grasping of Novel Objects using Vision
    • 818
    • PDF
    Real-time 3D model-based tracking using edge and keypoint features for robotic manipulation
    • 73
    • PDF
    Real-time tracking meets online grasp planning
    • D. Kragic, A. Miller, P. Allen
    • Computer Science
    • Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164)
    • 2001
    • 129
    • PDF
    Learning task error models for manipulation
    • 25
    • PDF
    RAPID - a video rate object tracker
    • 146
    • PDF
    KinectFusion: Real-time dense surface mapping and tracking
    • 3,069
    • PDF
    Efficient scene simulation for robust monte carlo localization using an RGB-D camera
    • 83
    • PDF
    Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
    • 1,322
    • PDF