This package provides python bindings to CUDA accelerated optical flow methods.
Taken from OpenCV 3.X 1. OpenCV must be installed on the machine.
To do: Write function to locate OpenCV on the machine without the use of pkg-config
.
@inproceedings{brox2004high,
title={High accuracy optical flow estimation based on a theory for warping},
author={Brox, Thomas and Bruhn, Andr{\'e}s and Papenberg, Nils and Weickert, Joachim},
booktitle={European conference on computer vision},
pages={25--36},
year={2004},
organization={Springer}
}
@inproceedings{bao2014cvpreppm,
title={Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow},
author={Bao, Linchao and Yang, Qingxiong and Jin, Hailin},
booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2014},
pages={3534-3541},
organization={IEEE}
}
git clone https://github.com/linchaobao/EPPM ~/EPPM
ln -s ~/EPPM .
python2 setup.py build_ext -i
python2 demo.py
1: https://docs.opencv.org/3.4.1/d7/d18/classcv_1_1cuda_1_1BroxOpticalFlow.html