How to automatically detect where a user is looking at, on a screen surface, in real-time.

What is it about?

Automatic gaze estimation not based on commercial and expensive eye tracking hardware solutions can enable several applications in the fields of human-computer interaction (HCI) and human behavior analysis. In this work, we propose a real-time user calibration-free gaze estimation system that does not need person-dependent calibration, can deal with illumination changes and head pose variations, and can work with a wide range of distances from the camera. Our solution is based on a 3-D appearance-based method that processes the images from a built-in laptop camera. Real-time performance is obtained by combining head pose information with geometrical eye features to train a machine learning algorithm.

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Why is it important?

Because very few camera-based systems proposed in the literature are both real-time and robust. In this work, we provided real user-computer interaction examples.

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