NO LONGER MAINTAINED, USE AT YOUR OWN RISK
GazeNet tracks the gaze location of a laptop user using the image from their webcam. Rather than collecting a large dataset of user data, GazeNet is trained using a combination of large synthetic or "fake" datasets and smaller dataset of real images.
Fake images are generated automatically using Unity3D. I make use of the free MCS Male character model to easily generate over 10,000 synthetic training images. Simulation is an easy way to generate large datasets
Real images are collected using a custom utility collect_gazedata.py
. This utility uses OpenCV to plot
gaze locations on the screen and takes a picture of the laptop user as they look at these gaze locations.
Real data collection is expensive and uses precious time.
collect_gazedata.py
to collect a real dataset. Follow the instructions in the pop-up.train_gazenet.py
to train a GazeNet (uses pre-trained feature extractors).run_gazenet.py
to run your GazeNet. Hopefully the green dot on the screen tracks your gaze![1] Learning from Simulated and Unsupervised Images through Adversarial Training. [2] Eye Tracking for Everyone