This software aims to provide an easy-to-compile C++ implementation of a 3D eye-tracking method.
Our software is designed for a wearable eye-tracking scnenario where a user wears a headset with an eye camera(s) that is equipped with infrared (IR) illuminations. The camera can capture close-up shots of the user's eyes.
With this software, you can obtain the following information:
Sample video on youtube (this was taken from a preliminary version and will be updated with a newer version soon).
Currently, the software is compatible with Visual Studio 2015. The test was done on a 64bit Windows 10 machine only.
Most of external libraries (for vc14, x64) are bundled in
./external, yet you still need to install the following two libraries: * OpenCV 3.1 * We recommend to use a windows installer (vc14, x64) * Boost C++ Libraries ver. >1.62 * We recommend to use a windows installer (boost162_0-msvc-14.0-64.exe)
[email protected]:YutaItoh/3D-Eye-Tracker.gitto your local folder (e.g.,
./CMakeLists.txtand edit the OpenCV path and the Boost path depending on your environment. For example, the default values are as follows:
/your-local-path/3D-Eye-Tracker) and a project build path (e.g.,
Generatebuttons, then choose a right build environment (Visual Studio 14 2015 Win64)
3d_eye_tracker.slnin the build folder, and compile
mainproject (recommend to set it as a startup project)
The default setting uses a sinlge camera via the DirectShow filter. Check your camera name on a video capture program (e.g., Skype) and set the name in
c++ case InputMode::CAMERA_MONO: eyecams=std::make_unique<:eyecamerads>("Pupil Cam1 ID0");In this case, the program tries to find a camera named
"Pupil Cam1 ID0".
Once the program started, it initializes a 3D eye model from 2D pupil observatios:
In this initialization step, a user needs to smoothly rotate his/her eye to capture various 2D shapes of the eye.
After the step, we get 3D eye tracking:
Some debug keys are pre-assigned for a better control of the software: *
p: Takes some more 2D pupil observations. Useful when estimated 3D eye model is incorrect due to not-well-distributed 2D observations *
r: Resets the 3D eye model and 2D observations and restarts the initialization step *
ESC: Exit the program