Calculate the dense optical flow using the DIS Algorithm from two images.
Updated 8 Aug 2017

Fast Optical Flow using Dense Inverse Search (DIS)# MATLAB Port of Fast Optical Flow using Dense Inverse Search (DIS) #
Our code is released only for scientific or personal use.
Please contact us for commercial use.

## Compiling ##
The program was only tested under a 64-bit Linux distribution.
SSE instructions from built-in X86 functions for GNU GCC were used.
The following will build four binaries:
Two for optical flow (`run_OF_*`) and two for depth from stereo (`run_DE_*`).
For each problem, a fast variant operating on intensity images (`run_*_INT`) and
a slower variant operating on RGB images (`run_*_RGB`) is provided.

make all

The code depends on Eigen3 OpenCV and MATLAB. However, OpenCV is only used for image loading,
scaling and gradient computation (`run_dense.cpp`). It can easily be replaced by other libraries.

Aditionally P. Dollar's toolbox is required for visualizing the flow. You can get it from [here](https://pdollar.github.io/toolbox/). This is only required for visualizing the flow not for calculating the flow. See `examples/example.m for more information`

## Usage ##
The interface for all four mex functions (`run_*_*()`) is the same.

VARIANT 1 (Uses operating point 2 of the paper, automatically selects coarsest scale):

` output = run_*_*(image1, image2 ) `

VARIANT 2 (Manually select operating point X=1-4, automatically selects coarsest scale):

` output = run_*_*(image1, image2, X) `

The optical flow output is a 2-D MATLAB matrix with x and y flows.

The interface for depth from stereo is exactly the same.

For more information refer to the ` example_1.m ` file in the examples folder.
## Bugs and extensions ##

If you find bugs, etc., please feel free to contact me at <zsameem@example.com>



## History ##

July 2016 v1.0.0 - Initial Release
August 2016 v1.0.1 - Minor Bugfix: Error in L1 and Huber error norm computation.


If used this work, please cite:

Author = {Till Kroeger and Radu Timofte and Dengxin Dai and Luc Van Gool},
Title = {Fast Optical Flow using Dense Inverse Search},
Booktitle = {Proceedings of the European Conference on Computer Vision ({ECCV})},
Year = {2016}} `

Is you use the variational refinement, please additionally cite:

` @inproceedings{weinzaepfelICCV2013,
TITLE = {{DeepFlow: Large displacement optical flow with deep matching}},
AUTHOR = {Weinzaepfel, Philippe and Revaud, J{\'e}r{\^o}me and Harchaoui, Zaid and Schmid, Cordelia},
BOOKTITLE = {{ICCV 2013 - IEEE International Conference on Computer Vision}},
YEAR = {2013}} `


GPLv3: http://gplv3.fsf.org/

All programs in this collection are free software:
you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.

Cite As

Samim Taray (2024). zsameem/OF_DIS (https://github.com/zsameem/OF_DIS), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2016b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

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To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.