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Implementation of "Non-linear Predictors for Facial feature Tracking across Pose and Expression" in Python

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reltracker

Implementation of: Tim Sheerman-Chase, Eng-Jon Ong, Richard Bowden. Non-linear Predictors for Facial feature Tracking across Pose and Expression. In IEEE Conference on Automatic Face and Gesture Recognition, Shanghai, 2013.

reltracker.py contains the main class RelTracker.

reltrackersimple.py is a simplified implementation without speed optimisation and less flexibility.

Dependancies

Python >=2.6, cython for optimized version.

Initial work for Python 3 compatibility started, but untested. Feedback welcome.

Usage

python setup.py build_ext --inplace

License

Copyright (C) 2013-2016 Tim Sheerman-Chase

This program is 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 2 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 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 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, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.

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Implementation of "Non-linear Predictors for Facial feature Tracking across Pose and Expression" in Python

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