Awesome
EpipolarScore
This repository is part of public implementation of our "Exploiting Geometric Constraints on Dense Trajectories for Motion Saliency" paper. This repository contains Optical Flow & Epipolar Score Computation code. You can check the main repository here.
Installations:
This source code is based on MATLAB framework and tested on Ubuntu 16.04 with MATLAB 2016b.
Instructions:
1) Clone the repository
git clone https://github.com/mfaisal59/EpipolarScore.git
2) Download Dataset
Download and unpack the DAVIS 2016 dataset and as well as the evaluatio code from https://davischallenge.org/davis2016/code.html
3) Compute Optical Flow
The optical flow is based on Full Flow Method (https://cqf.io/fullflow/). To compute the optical flow for DAVIS Dataset, run the following script:
cd ./Full_Flow_Source_Code/
run davisBatch.m file
#modify the path to DAVIS dataset directory
4) Compute Epipolar Score
To compute the Epipolar Score, modify the paths in 'testDAVIS.m' file and run:
cd ./EpipolarScoreMain/
run testDAVIS.m script
#modify the path to DAVIS dataset, forward and backward optical flow directory
5) Convert Flow to X-Y Displacement Images
cd ./EpipolarScoreMain/
run flow2Displacement.m script
#modify the paths to DAVIS dataset, forward and backward optical flow directory
6) Generate Motion Images
cd ./EpipolarScoreMain/
run generateMotionImages.m script
#modify the paths to DAVIS dataset and Optical Flow directory
BIBTEX:
@article{DBLP:journals/corr/abs-1909-13258,
author = {Muhammad Faisal and
Ijaz Akhter and
Mohsen Ali and
Richard I. Hartley},
title = {Exploiting Geometric Constraints on Dense Trajectories for Motion
Saliency},
journal = {CoRR},
volume = {abs/1909.13258},
year = {2019},
url = {http://arxiv.org/abs/1909.13258}
}