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SDRSAC - Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences.

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SDRSAC

MATLAB implementation of the following CVPR'19 paper:

  • SDRSAC - Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences.- Huu Le, Thanh-Toan Do, Tuan Hoang, and Ngai-Man Cheung (Oral).

Paper can be accessed at: https://arxiv.org/pdf/1904.03483v1.pdf

Before running the demo, please download the latest version of SDPNAL+ (https://drive.google.com/open?id=1wE90nFu95Lq4AOazq_rTaI6D70h4NhK-) and extract the zip file to /solvers/SDPNAL+v1.0/ (you can overwrite the existing folder)

Run demo_sdrsac.m to start the demo.

Notes:

  • Currently, SDPNAL++ (provided in the solver folder) is used as the default solver. Better solvers can be replaced to improve the performance.
  • The implementation of known correspondences will be available soon.
  • Tests with real-data will be added.

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SDRSAC - Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences.

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