README.md

PrimiTect: Fast Continuous Hough Voting for Primitive Detection

This repository provides the code accompanying the paper PrimiTect: Fast Continuous Hough Voting for Primitive Detection by C. Sommer, Y. Sun, E. Bylow and D. Cremers, presented at the International Conference on Robotics and Automation (ICRA) 2020. A preprint can be found on arXiv.

Basic Usage

We provide detailed information on how to build, compile and run our code in the cpp folder containing the code.

Data

See the folder data for information and scripts to generate the data we used in our paper.

Visualization of Results

The figures in our paper can be reproduced using the Matlab visualization files provided in visualization. We also provide example data (in data/) together with example results (in ex_results) which can be directly used to test the visualization functions. Simply cd into visualization/, open Matlab and run the script VisualizeExampleResults.

License and Publication

Our code is released under the GPL (v3+) license, for more details please see the LICENSE file. Also note the different licenses of the submodules in the folder thirdparty.

Please cite our paper when using the code in a scientific project. You can copy-paste the following BibTex entry:

@inproceedings{sommer2020,
    title   = {PrimiTect: Fast Continuous Hough Voting for Primitive Detection},
    author  = {Sommer, Christiane and Sun, Yumin and Bylow, Erik and Cremers, Daniel},
    booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
    year    = {2020},
    doi = {10.1109/ICRA40945.2020.9196988}
}