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Some changes in the readme.

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Tadas Baltrusaitis 2017-12-29 08:01:51 +00:00
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[![Build Status](https://travis-ci.org/TadasBaltrusaitis/OpenFace.svg?branch=master)](https://travis-ci.org/TadasBaltrusaitis/OpenFace) [![Build Status](https://travis-ci.org/TadasBaltrusaitis/OpenFace.svg?branch=master)](https://travis-ci.org/TadasBaltrusaitis/OpenFace)
[![Build status](https://ci.appveyor.com/api/projects/status/8msiklxfbhlnsmxp/branch/master?svg=true)](https://ci.appveyor.com/project/TadasBaltrusaitis/openface/branch/master) [![Build status](https://ci.appveyor.com/api/projects/status/8msiklxfbhlnsmxp/branch/master?svg=true)](https://ci.appveyor.com/project/TadasBaltrusaitis/openface/branch/master)
Over the past few years, there has been an increased interest in automatic facial behavior analysis and understanding. We present OpenFace – an open source tool intended for computer vision and machine learning researchers, affective computing community and people interested in building interactive applications based on facial behavior analysis. OpenFace is the first open source tool capable of facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation. The computer vision algorithms which represent the core of OpenFace demonstrate state-of-the-art results in all of the above mentioned tasks. Furthermore, our tool is capable of real-time performance and is able to run from a simple webcam without any specialist hardware. Over the past few years, there has been an increased interest in automatic facial behavior analysis and understanding. We present OpenFace – a tool intended for computer vision and machine learning researchers, affective computing community and people interested in building interactive applications based on facial behavior analysis. OpenFace is the first toolkit capable of facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation with available source code. The computer vision algorithms which represent the core of OpenFace demonstrate state-of-the-art results in all of the above mentioned tasks. Furthermore, our tool is capable of real-time performance and is able to run from a simple webcam without any specialist hardware.
The code was written mainly by Tadas Baltrusaitis during his time at the Language Technologies Institute at the Carnegie Mellon University; Computer Laboratory, University of Cambridge; and Institute for Creative Technologies, University of Southern California. ![Multicomp logo](https://github.com/TadasBaltrusaitis/OpenFace/blob/master/imgs/muticomp_logo_black.png)
Special thanks goes to Louis-Philippe Morency and his MultiComp Lab at Institute for Creative Technologies for help in writing and testing the code, and Erroll Wood for the gaze estimation work. ![Rainbow logo](https://github.com/TadasBaltrusaitis/OpenFace/blob/master/imgs/rainbow-logo.gif)
OpenFace is an implementation of a number of research papers from the Multicomp group, Language Technologies Institute at the Carnegie Mellon University and Rainbow Group, Computer Laboratory, University of Cambridge. The founder of the project and main developer is Tadas Baltrušaitis.
Special thanks goes to Louis-Philippe Morency and his MultiComp Lab at Carnegie Mellon University for help in writing and testing the code, and Erroll Wood for the gaze estimation work.
## WIKI ## WIKI
**For instructions of how to install/compile/use the project please see [WIKI](https://github.com/TadasBaltrusaitis/OpenFace/wiki)** **For instructions of how to install/compile/use the project please see [WIKI](https://github.com/TadasBaltrusaitis/OpenFace/wiki)**
More details about the project - http://www.cl.cam.ac.uk/research/rainbow/projects/openface/
## Functionality ## Functionality
The system is capable of performing a number of facial analysis tasks: The system is capable of performing a number of facial analysis tasks:
@ -68,12 +70,6 @@ Tadas Baltrušaitis, Marwa Mahmoud, and Peter Robinson
in *Facial Expression Recognition and Analysis Challenge*, in *Facial Expression Recognition and Analysis Challenge*,
*IEEE International Conference on Automatic Face and Gesture Recognition*, 2015 *IEEE International Conference on Automatic Face and Gesture Recognition*, 2015
# Copyright
Copyright can be found in the Copyright.txt
You have to respect boost, TBB, dlib, OpenBLAS, and OpenCV licenses.
# Commercial license # Commercial license
For inquiries about the commercial licensing of the OpenFace toolkit please contact innovation@cmu.edu For inquiries about the commercial licensing of the OpenFace toolkit please contact innovation@cmu.edu
@ -82,3 +78,10 @@ For inquiries about the commercial licensing of the OpenFace toolkit please cont
I did my best to make sure that the code runs out of the box but there are always issues and I would be grateful for your understanding that this is research code and not full fledged product. However, if you encounter any problems/bugs/issues please contact me on github or by emailing me at Tadas.Baltrusaitis@cl.cam.ac.uk for any bug reports/questions/suggestions. I prefer questions and bug reports on github as that provides visibility to others who might be encountering same issues or who have the same questions. I did my best to make sure that the code runs out of the box but there are always issues and I would be grateful for your understanding that this is research code and not full fledged product. However, if you encounter any problems/bugs/issues please contact me on github or by emailing me at Tadas.Baltrusaitis@cl.cam.ac.uk for any bug reports/questions/suggestions. I prefer questions and bug reports on github as that provides visibility to others who might be encountering same issues or who have the same questions.
# Copyright
Copyright can be found in the Copyright.txt
You have to respect boost, TBB, dlib, OpenBLAS, and OpenCV licenses.
Furthermore you have to respect the licenses of the datasets used for model training - https://github.com/TadasBaltrusaitis/OpenFace/wiki/Datasets