Real-time pose estimation of deformable objects using a volumetric approach

@article{Li2014RealtimePE,
  title={Real-time pose estimation of deformable objects using a volumetric approach},
  author={Yinxiao Li and Yan Wang and Michael Case and Shih-Fu Chang and Peter K. Allen},
  journal={2014 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year={2014},
  pages={1046-1052}
}
Pose estimation of deformable objects is a fundamental and challenging problem in robotics. We present a novel solution to this problem by first reconstructing a 3D model of the object from a low-cost depth sensor such as Kinect, and then searching a database of simulated models in different poses to predict the pose. Given noisy depth images from 360-degree views of the target object acquired from the Kinect sensor, we reconstruct a smooth 3D model of the object using depth image segmentation… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 30 CITATIONS

References

Publications referenced by this paper.
SHOWING 1-10 OF 25 REFERENCES

Similar Papers

Loading similar papers…