Building on Windows Visual Studio

Prerequisites

• Install Visual Studio 2013:

  Note: Visual Studio Express and Visual Studio 2015 are not supported! Update(2016.6): Now CUDA 8 RC could support VS2015 Update 1

  Nvidia reference

• Install Cuda 7.5: Also refer to above link. download

• Install CMake: The latest version is OK. download

• Install OpenCV: I installed 3.1, other versions should also work. download

  • Run the EXE to extract the files. This EXE does not have an installer. Instead, you put your files where you want, and then add an environment variable
  • Adding the environment variable named "OpenCV_DIR" (no quotes) to the "build" subfolder in the folder where you extracted.(The exact folder you need will have one very important file in it: OpenCVConfig.cmake - this tells CMake which variables to set for you.)
  • Add a dir of "OpenCV binary DLLs" to Windows $PATH.(like f:/software/opencv/build/x64/vc12/bin)
  • If we run CUDA build, Opencv should be recompiled with CUDA options on, as the pre-built version does not support CUDA functions. Options suggested:
    • -DWITH_CUDA=ON -DBUILD_DOCS=OFF -DBUILD_TESTS=OFF -DBUILD_PERF_TESTS=OFF -DBUILD_SHARED_LIBS=OFF -DBUILD_WITH_STATIC_CRT=OFF -DBUILD_opencv_apps=OFF -DWITH_TBB=ON -DWITH_OPENMP=ON -DWITH_IPP=ON

Compile the solution

• Use the cmake-gui tool:

  Open the cmake-gui tool and selete the location of Source and Build. Then press configure to specify the generator: In this case, it's Visual Studio 12 2013 Win64. Last, press generate.

• Use the cmake command line:

  mkdir build && cd build/ && cmake -G "Visual Studio 12 2013 Win64"

Done! Just use Visual Studio to open the project-solution in dir build/ and compile everything.

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Original README.md

AprilTags library

Detect April tags (2D bar codes) in images; reports unique ID of each detection, and optionally its position and orientation relative to a calibrated camera.

See examples/apriltags_demo.cpp for a simple example that detects April tags (see tags/pdf/tag36h11.pdf) in laptop or webcam images and marks any tags in the live image.

Ubuntu dependencies: sudo apt-get install subversion cmake libopencv-dev libeigen3-dev libv4l-dev

Mac dependencies: sudo port install pkgconfig opencv eigen3

Uses the pods build system in connection with cmake, see: http://sourceforge.net/p/pods/

Michael Kaess October 2012

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AprilTags were developed by Professor Edwin Olson of the University of Michigan. His Java implementation is available on this web site: http://april.eecs.umich.edu.

Olson's Java code was ported to C++ and integrated into the Tekkotsu framework by Jeffrey Boyland and David Touretzky.

See this Tekkotsu wiki article for additional links and references: http://wiki.tekkotsu.org/index.php/AprilTags

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This C++ code was further modified by Michael Kaess (kaess@mit.edu) and Hordur Johannson (hordurj@mit.edu) and the code has been released under the LGPL 2.1 license.

• converted to standalone library
• added stable homography recovery using OpenCV
• robust tag code table that does not require a terminating 0 (omission results in false positives by illegal codes being accepted)
• changed example tags to agree with Ed Olson's Java version and added all his other tag families
• added principal point as parameter as in original code - essential for homography
• added some debugging code (visualization using OpenCV to show intermediate detection steps)
• added fast approximation of arctan2 from Ed's original Java code
• using interpolation instead of homography in Quad: requires less homography computations and provides a small improvement in correct detections

todo:

• significant speedup could be achieved by performing image operations using OpenCV (Gaussian filter, but also operations in TagDetector.cc)
• replacing arctan2 by precomputed lookup table
• converting matrix operations to Eigen (mostly for simplifying code, maybe some speedup)