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RANSAC variant for 3D object recognition in occluded scenes.
This project forked from tum-mvp/objrecransac
RANSAC variant for 3D object recognition in occluded scenes.
#################################################################### # # # ObjRecRANSAC - RANSAC variant for 3D object recognition in # # occluded scenes # # # # Chavdar Papazov ([email protected]) # # Darius Burschka ([email protected]) # # # #################################################################### 1. Introduction. Thank you for taking interest in our work and downloading this software. This software implements a modified version of the algorithm described in the papers * Chavdar Papazov and Darius Burschka: "An Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes". In Proceedings of the 10th Asian Conference on Computer Vision (ACCV'10), 2010 * Chavdar Papazov, Sami Haddadin, Sven Parusel, Kai Krieger, and Darius Burschka: "Rigid 3D Geometry Matching for Grasping of Known Objects in Cluttered Scenes". International Journal of Robotics Research, 31, April 2012. If you use this software please cite the aforementioned papers in any resulting publication. Please send questions, comments and/or bug reports to Chavdar Papazov ([email protected]) The software was tested on 64bit Linux (Fedora 12 and Ubuntu 11.10). ################################################################## 2. License & disclaimer. Copyright 2011-212 Chavdar Papazov ([email protected]) Darius Burschka ([email protected]) This software may be used for research purposes only. Do not redistribute. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. This software contains source code provided by NVIDIA Corporation. ################################################################## 3. How to build and run. 1. Install cmake (www.cmake.org), VTK (www.vtk.org) and OpenCV 2. Go to the folder build (using the command line) 3. Type ccmake .. 3.1. Press c (for configure) 3.2. Set CMAKE_BUILD_TYPE to Release 3.3. Press c again 3.4. Press g (for generate) 4. Type make 5. Type ./ObjRecRANSACRun to run the program 6. After the computations are performed a window should pop up showing the result of the recognition. It should be similar to the image typical_result.png in the main folder. You can navigate in the scene using the mouse. ################################################################## 4. Some additional comments. The image typical_result.png shows a result of the recognition using the data sets in the data folder. The gray points show the detected plane and are not used for the recognition. The blue points are the non-plane points used for the recognition. The orange meshes are representing the recognized model instances in the scene. Check the main.cpp file to see how to use the algorithm. Note that the recognition is based on a stochastic method, i.e., it produces each time a different result.
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