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This is the software bundle "InfiniTAM", created and maintained by:

Victor Adrian Prisacariu [email protected] Olaf Kaehler [email protected] Ming Ming Cheng [email protected] Carl Yuheng Ren [email protected] Julien Valentin [email protected] Philip H.S. Torr [email protected] Ian D Reid [email protected] David W Murray [email protected]

1. Building the System

1.1 Requirements

Several 3rd party libraries are needed for compiling InfninTAM. 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.

• cmake (e.g. version 2.8.10.2) 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) REQUIRED for the visualisation the library should run without available at http://freeglut.sourceforge.net/

• CUDA (e.g. version 6.0) OPTIONAL but REQUIRED for all GPU accelerated code at least with cmake it is still possible to compile the CPU part without available at https://developer.nvidia.com/cuda-downloads

• OpenNI (e.g. version 2.2.0.33) OPTIONAL but REQUIRED to get live images from the suitable hardware also make sure you have freenect/OpenNI2-FreenectDriver if you need it available at http://structure.io/openni

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

1.2 Build Process

To compile the system, use the standard cmake approach:

$ mkdir build $ cd build $ cmake /path/to/InfiniTAM -DOPEN_NI_ROOT=/path/to/OpenNI2/ $ make

To create a doxygen documentation, just run doxygen:

$ doxygen Doxyfile

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

1.3 Odds and Ends

Padding the data structure ITMVoxel in ITMLibDefines.h with one extra byte may or may not improve the overall performance on certain GPUs. On a NVidia GTX 680 it appears to do, on a GTX 780 it does not. Have a try yourself if you need the speed.

On Mac OS X 10.9 there are currently some issues with libc++ vs. libstdc++ in conjunction with CUDA. They eventually manifest in error messages like: " Undefined symbols for architecture x86_64: "std::ios_base::Init::Init()", referenced from: __GLOBAL__I_a in libITMLib.a(ITMLib_generated_ITMColorTracker_CUDA.cu.o) __GLOBAL__I_a in libITMLib.a(ITMLib_generated_ITMDepthTracker_CUDA.cu.o) [...] " In the current version of InfiniTAM these errors are avoided by specifying CMAKE_CXX_FLAGS=-stdlib=libstdc++ whenever clang is detected as complier. However, future versions of CUDA might not require this anymore or even get confused and/or require CUDA_HOST_COMPILER=/usr/bin/clang instead.

If a version of GLUT other than freeglut is used, the InfiniTAM sample application has problems on exit, as it is currently not explicitly cleaning up CUDA memory or closing the OpenNI device. Use freeglut to avoid this if you experience any problems.

2. Sample Programs

The build process should result in an executable InfiniTAM, which is the main and only sample program. If compiled with OpenNI support, it should run out-of-the-box without problems for live reconstruction. If you have calibration information for your specific device, you can pass it as the first argument to the program, e.g.:

$ ./InfiniTAM Teddy/calib.txt

If no OpenNI support has been compiled in, the program can be used for offline processing:

$ ./InfiniTAM Teddy/calib.txt 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.

3. Additional Documentation

Apart from the doxygen documentation there should be a technical report shipped along with this package. It is also available from the official project website.

History:

2014-OCT-06: initial public release