A real time optical flow algorithm implemented on GPU.
@Article{2016_Adarve_RAL,
Title = {A Filter Formulation for Computing Real Time Optical Flow},
Author = {{Juan David} Adarve and Robert Mahony},
Journal = {Robotics and Automation Letters},
Year = {2016}
}
- CMake 2.8.11 or higher
- Cuda 7.5
- Visual Studio 2013 (Windows only)
git clone https://github.com/jadarve/optical-flow-filter.git
cd optical-flow-filter
mkdir build
cd build
cmake ..
make
sudo make install
The library and header files will be installed at /usr/local/lib and /usr/local/include respectively.
mkdir build64 & cd build64
cmake -G "Visual Studio 12 2013 Win64" ..
cmake --build . --config Release
mkdir build & cd build
cmake -G "Visual Studio 12 2013"
cmake --build . --config Release
##Python Wrappers
A python package with wrappers to the C++ library is available at optical-flow-filter/python/ folder. The wrappers have been developed and build using Cython 0.23.4.
cd optical-flow-filter/python/
python setup.py build
sudo python setup.py install
See notebooks/ folder for usage examples.
This demo computes optical flow from a webcam. It uses OpenCV to access the camera video stream and to display the computed flow. The instructions to build the demo are the following:
cd optical-flow-filter/demos/flowWebCam
mkdir build
cd build
cmake ..
make
./flowWebCam
This demo interfaces a Basler camera, in our case an acA2000-165um, with the GPU optical flow algorithm, and displays the color encoded flow.
cd optical-flow-filter/demos/highSpeedDemo
mkdir build
cd build
cmake ..
make
To run the application, it is necessary to specify the camera properties file, as follows
./highSpeedDemo -c ../acA2000-165um_binSkip.pfs
Other optional arguments are:
./highSpeedDemo -h
-h, --help Displays this help.
-v, --version Displays version information.
-c, --config <file> Camera configuration file.
-l, --levels <int> Flow filter pyramid levels (default 2).
-r, --rate <int> Camera frame rate (default 300).
-m, --maxflow <float> Maximum optical flow (default 4.0).