Skip to content


Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?

Latest commit


Git stats


Failed to load latest commit information.
Latest commit message
Commit time

KFusion 0.4

Copyright TU Graz, Gerhard Reitmayr, 2011 - 2013

This is an implementation sketch of the KinectFusion system described by Richard Newcombe et al. in "KinectFusion: Real-Time Dense Surface Mapping and Tracking", ISMAR 2011, 2011. It is a dense surface reconstruction and tracking framework using a single Kinect camera as the input sensor.

KFusion is mainly written in CUDA with some interface code to display graphics output.


KFusion depends on the following libraries:

On Windows use the MS Kinect SDK:

while on other platforms use libfreenect:

and of course the CUDA 5 SDK by NVidia


Use CMake to create build files for your platform. Some tips and tricks

  • On Windows, make sure to use a 64-bit version of GLUT
  • On Apple OSX, set CUDA_HOST_COMPILER to /usr/bin/g++

Altenatively, On Unix/OSX platforms, tweak the Makefile for your setup, then make.

Have a look at kfusion.h for a description of most parameters and kinect.cpp for setting them.


  • rendering
    • integrate with GL for additional 3D graphics
  • write an inverse tracking method that moves the camera in the system
  • save size through combined depth + 2D normal maps


  • MSKinect SDK interface for Windows, libfreenect on other platforms
  • rendering with static model view + projected RGB + interactive viewpoint
  • registered depth input from libfreenect, uses more time unfortunately
  • integration speed up
  • CMake build system (contributed by Hartmut Seichter)
  • fixed a substantial bug in tracking
  • improved raycasting by an implementation closer to the paper. This also seems to take care of the following issue:
    • tracking works much better with a detailed model and sharp bounds on normals (0.9), problem for low resultion ?
  • replaced libcvd with GLUT in the master branch
  • created dedicated Image class templated on different memory locations, reduces most dependencies on libcvd
  • removed all 3D grids to reduce code and maybe speed up as well
  • 2D grid for volume integration is 40% faster
  • fixed a difference in computing normals in raycasting and from kinect input... maybe influences tracking ?
  • added a combined tracking & reduce implementation that saves a bit of time
  • make configuration more automatic, compute dependent variables, scales for tracking
  • make a version that uses one volume for both SDF + weight
    • split 32bit into 16bit float [-1,-1] and unsigned int for weight
  • scaling for better optimization, didn't really do much, removed it again
  • multi level tracking
  • split
    • core operations
    • testing with extra volume etc
    • rendering
    • make OO ?
  • speed up raycasting with mu step sizes
  • reduction somewhat better through local memory -> shared memory
  • test larger volume sizes
    • 3D operations over 2D grid - works nicely !
  • pitched images no change, because they are already all pitched !
  • template volume on data type and convert to/from float on the fly - did not change speed at all !
  • ambient lighting
  • bilateral filtering


Hartmut Seichter


This is an implementation sketch of the KinectFusion system described by Newcombe et al.







No releases published


No packages published