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According to the CBS news report, "if you use a computer more than two hours a day, you could be suffering from Computer Vision Syndrome (CVS)".
The project's main objective is making a software that will help us protect our eyes from CVS.
This is a set of computer vision/camera control/mathematical algorithms based on and implementations based on OpenCV used by me for educational and research purposes.
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Computer vision tracking module written in C++ as an extension to OpenCV, this code is the foundation for the "Are We There Yet?" installation by Ken Goldberg and Gil Gershoni in the Contemporary Jewish Museum Mar 31 - Jul 31 2011.
OpenCV-AR is a software library used for Augmented Reality development. It is targeted on Linux, though it is also able to work on Windows platform. It is an alternative to ARToolKit for Augmented Reality application development.
EStereo is a computer vision C++ library for real-time disparity estimation. It computes dense stereo matching from 2 or 3 images as well as 3D scene reconstruction. The library also comes with a GUI-based application (StereoPlus).
The Python Computer Vision Framework is an opened project deisgned for all those interested in computer vision. It aims at making computer vision more easy and structured and matlab-free.
It may also be used for other artistic and scientific areas.
The Tensor Voting Framework is a powerful technique for perceptual grouping, manifold learning, etc. It has proved to be a useful tool in the Computer Vision community. OpenTVF is an open source implementation of TVF.
PyCV is a Python package of modules useful for computer vision tasks. Its current focus is on boosting techniques, Haar-like features, and face detection. PyCV provides the world's fastest method for training a face detector, in a few hours.
The STAIR Vision Library (SVL), originally developed to support the STanford AI Robot, provides software infrastructure for computer vision, machine learning, and probabilistic graphical models.
A photo gallery management system based on hand gesture recognition. You must make three color markers by yourself, which the red one on index of the right hand, the green one on thumb of the right hand and the blue one on index of the left hand.