Fast dense stereo correspondences by binary locality sensitive hashing

@article{Heise2015FastDS,
  title={Fast dense stereo correspondences by binary locality sensitive hashing},
  author={Philipp Heise and Brian Jensen and Sebastian Klose and Alois Knoll},
  journal={2015 IEEE International Conference on Robotics and Automation (ICRA)},
  year={2015},
  pages={105-110}
}
The stereo correspondence problem is still a highly active topic of research with many applications in the robotic domain. Still many state of the art algorithms proposed to date are unable to reasonably handle high resolution images due to their run time complexities or memory requirements. In this work we propose a novel stereo correspondence estimation algorithm that employs binary locality sensitive hashing and is well suited to implementation on the GPU. Our proposed method is capable of… CONTINUE READING

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