/MeshHashingDTSDF

Implementation of our paper "Directional TSDF: Modeling Surface Orientation for Coherent Meshes"

Primary LanguageCuda

MeshHashingDTSDF

Accompanying code for our IROS 2019 paper

@InProceedings{DTSDF_IROS_2019,
  author    = {M. {Splietker} and S. {Behnke}},
  title     = {Directional {TSDF}: Modeling Surface Orientation for Coherent Meshes},
  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year      = {2019},
  pages     = {1727--1734}
}

This project is deprecated in favor of our new implementation

This code is a fork of the original MeshHashing by Dong et al. Please make sure to cite our and their corresponding papers, if you use the code.

Build Instructions:

Because the code used GPU accelerated code, it requires OpenCV to be build with WITH_CUDA=ON. You may need to set the OpenCV_DIR variable in CMakeLists.txt.

sudo apt install libglfw3-dev ros-melodic-sophus libglm-dev libcapnp-dev
git submodule update --init --recursive 
mkdir build
cd build
cmake ..
make 

You might experience some warnings or errors originating from compiling Eigen with CUDA. In that case use a more recent Eigen version (>= 3.3.9).

Usage

cd bin
./reconstruction

The program is controlled by the config file config/args.yml and accompanying dataset config specified by the dataset_type field. E.g. dataset_type: 3 corresponds to the config file config/TUM3.yml for datasets in the TUM fr3 format.