Directional TSDF InfiniTAM

This repository contains an implementation of Directional TSDF (DTSDF) and is based on InfiniTAM v3. If you use our code for your publications, please cite our work (see Research)

• The original InfiniTAM code was heavily modified

Previous maintainers and contributors are:

Malte Splietker
Victor Adrian Prisacariu victor@robots.ox.ac.uk
Olaf Kaehler olaf@robots.ox.ac.uk
Stuart Golodetz smg@robots.ox.ac.uk
Michael Sapienza michael.sapienza@eng.ox.ac.uk
Tommaso Cavallari tommaso.cavallari@unibo.it
Carl Yuheng Ren carl@robots.ox.ac.uk
Ming Ming Cheng cmm.thu@gmail.com
Xin Sun xin.sun@st-hughs.ox.ac.uk
Philip H.S. Torr philip.torr@eng.ox.ac.uk
Ian D Reid ian.reid@adelaide.edu.au
David W Murray dwm@robots.ox.ac.uk

1. Building the System

1.1 Requirements

Several 3rd party libraries are needed for compiling InfiniTAM. The given version numbers are checked and working, but different versions might be fine as well. Some of the libraries are optional, and skipping them will reduce functionality.

Required

• cmake (e.g. version 2.8.10.2 or 3.2.3) Required for Linux, unless you write your own build system OPTIONAL for MS Windows, if you use MSVC instead available at http://www.cmake.org/

• OpenGL / GLUT (e.g. freeglut 2.8.0 or 3.0.0) Required for the visualisation. Library and command line app should run without available at http://freeglut.sourceforge.net/

• CUDA (e.g. version 9.0 or 10.0) Required for all GPU accelerated code (CPU only version currently defunct) available at https://developer.nvidia.com/cuda-downloads

Optional

• OpenNI (e.g. version 2.2.0.33) Allows get live images from OpenNI hardware. Also make sure you have freenect/OpenNI2-FreenectDriver if you need it available at http://structure.io/openni

• libpng (e.g. version 1.6) Allows to read and write PNG files available at http://libpng.org

• FFMPEG (e.g. version 2.8.6) Allows writing and playback of lossless FFV1 encoded videos available at https://www.ffmpeg.org/

• librealsense (e.g. github version from 2016-MAR-22) Allows to get live images from Intel Realsense cameras available at https://github.com/IntelRealSense/librealsense

• librealsense2 (e.g. Intel® RealSense™ SDK 2.X) Allows to get live images from Intel Realsense cameras available at https://github.com/IntelRealSense/librealsense

• doxygen (e.g. version 1.8.2) Builds a nice reference manual available at http://www.doxygen.org/

1.2 Build Process

To compile the system, use the standard cmake approach (use options for required input devices, e.g. by using ccmake). For example

git submodule update --init --recursive
mkdir build
cd build
cmake -DWITH_PNG=ON -DWITH_OPENNI=ON -DWITH_REALSENSE2=ON -DREALSENSE2_ROOT="/usr/" -DOPENNI_ROOT="/usr/" -DWITH_KINECT2=ON ..
make

To create a doxygen documentation, just run doxygen:

doxygen Doxyfile

This will create a new directory doxygen-html/ containing all the documentation.

2. Sample Programs

The build process should result in two executables, InfiniTAM and InfiniTAM_cli. The former is a GUI, the latter a headless command line application. If compiled with for example OpenNI support, both should run out-of-the-box without problems for live reconstruction. All available command line options are printed using the --help flag. If no device support has been compiled in, the program can be used for offline processing. For raw datasets in the form of

path/to/InfiniTAM Teddy/calib.txt --settings ./Files/settings.yaml --raw Teddy/Frames/%04i.ppm Teddy/Frames/%04i.pgm

The arguments are essentially masks for sprintf and the %04i will be replaced by a running number, accordingly.

Datasets in TUM format are also supported. Here is an example for a dataset from the fr3 sequences. (Note: the dataset's rgb.txt and depth.txt must only contain matched pairs of rgb and depth images.

path/to/InfiniTAM --calibration ./Files/TUM3.txt --settings ./Files/settings.yaml --tum /path/to/dataset

The calibration files (e.g. .Files/TUM3.txt) contain camera calibrations specific for each datasets. Many live input sources like OpenNI2 automatically provide their intrinsics via the respective library. The file ./Files/settings.yaml contains algorithm parameters like voxel size, allocation sizes tracking parameters etc.

Statistics and other output are written in the Output directory of the present working director, if it exists.

3. Research

Original paper (IROS 2019) introducing the Directional TSDF and modified Marching Cubes algorithm. PDF

@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}
}

Most recent paper (ECMR 2021) including ray-casting rendering, combined TSDF, ICP tracking and color fusion. PDF

@misc{DTSDF_IROS_2021,,
      title={Rendering and Tracking the Directional {TSDF}: Modeling Surface Orientation for Coherent Maps}, 
      author={Malte {Splietker} and Sven {Behnke}},
      year={2021},
      eprint={2108.08115},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

For more information about the original InfiniTAM please visit the project website http://www.infinitam.org.