Gaze aims at providing an easy to use gaze tracking library. It was the project for my master's thesis. Inspired by eyeLike, it performs eye tracking well.
Warning: Gaze tracking does not work!
But you can try the GazeCapture
pipeline step by modifying the gaze.yaml
and configuring Gaze with --caffe
. However, since the underlying CNN is trained on iPhone and iPad screens, it is most accurate in a smaller screen area around the camera.
If you are interested in picking up the project or have some ideas on how to best fix the gaze tracking, make sure to drop me a line! shoeffner@uos.de
You need the following dependencies to build gaze (tested versions in parentheses):
For the examples/demo projects you need:
For the documentation you need:
For the development you need:
Optional:
To build gaze, simply run
./configure.sh
cd build
make install
configure.sh
comes with some options:
--release
: Enables compiler optimizations--debug
: Disables compiler optimizations, builds debug symbols and creates verbose makefiles.--examples
: Configures cmake to create build files for the examples.--doc
: Configures cmake to create build files for the documentation.--tagfiles
: Links the documentation to other projects (OpenCV and the C++ standard library)--dry
: Just prints the cmake ..
command without executing it--caffe
: Enables a build with Caffe support. This allows to use the experimental pipeline step GazeCapture
.where_people_look
This is a reimplementation of Judd et al. (2009)'s data acquisition experiment @cite Judd2009.
It needs to be installed using make install
to put the images into the
correct location. You can run it by simply typing ./where_people_look
from
the build directory.
simple_tracking
This program just starts a small window with an "experiment" and tracks gaze. Starts the gaze tracker in debug mode to see what is tracked.
Install cpplint.
Add a pre-commit hook (.git/hooks/pre-commit
):
cpplint --recursive --extensions cpp,h --quiet src tests include
Gaze is released under the MIT License.
But it cannot be used for commercial use without a modification, quoting from dlib-model's README:
The license for this dataset excludes commercial use and Stefanos Zafeiriou, one of the creators of the dataset, asked me to include a note here saying that the trained model therefore can’t be used in a commerical product.
Since this model is used in Gaze, no commercial use is possible.
The GazeCapture
pipeline makes use of the
CNN iTracker by Krafka et al., which also
only allows research usage.