_EyeTab_ is a __3D model-based gaze tracker__ that runs entirely on unmodified commodity tablet computers, taking their limited computational resources and low quality cameras into account.
*`EyeTab_Python`– A previous iteration of the system written in Python. This was developed rapidly as a prototype so is only included for your curiosity, it is not documented or supported.
The project's webpage can be found [here](http://www.cl.cam.ac.uk/research/rainbow/projects/eyetab/).
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A video of the system in action (Python version) can be seen [here](https://www.youtube.com/watch?v=lPcjQdSzKX4).
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###Publication
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*Erroll Wood and Andreas Bulling. 2014. EyeTab: model-based gaze estimation on unmodified tablet computers. In Proceedings of the Symposium on Eye Tracking Research and Applications (ETRA '14)* [[available at ACM-DL]](http://dl.acm.org/citation.cfm?id=2578185&CFID=433705372&CFTOKEN=17651040)
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If you use or extend EyeTab code in full or in part, please cite the paper above.
We track gaze by modelling the iris as a 2D ellipse in an image, and _back-projecting_ this to a 3D circle, getting the real-world position and orientation of the iris. We take the normal vector of this to be the gaze direction.
1. Open the solution file `EyeTab.sln` in Visual Studio. I used VS2012.
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2. Add dependencies to Visual Studio' _Additional include directories_ field, _Additional library directories_ field, and as _Additional input_ in the linker.
In addition, the SP2 version of the system depends on [VideoInput](// see: http://www.codeproject.com/Articles/559437/Capturing-video-from-web-camera-on-Windows-and) for providing high-resolution access to the front-facing camera. OpenCV's camera API is broken and does not support this. This library `videoInput.lib` is supplied.
