Communication via Eye Blinks — Detection and Duration Analysis in Real Time

Kristen Grauman, Massachusetts Institute of Technology

Photo of Kristen Grauman

A method for a real-time vision system that automatically detects a user’s eye blinks and accurately measures their durations is introduced. The system is intended to provide an alternate input modality to allow people with severe disabilities to access a computer. Voluntary long blinks trigger mouse clicks, while involuntary short blinks are ignored. The system enables communication using “blink patterns”: sequences of long and short blinks which are interpreted as semiotic messages. The location of the eyes is determined automatically through the motion of the user’s initial blinks. Subsequently, the eye is tracked by correlation across time, and appearance changes are automatically analyzed in order to classify the eye as either open or closed at each frame. No manual initialization, special lighting, or prior face detection is required. The system has been tested with interactive games and a spelling program. Results demonstrate overall detection accuracy of 95.6% and an average rate of 28 frames per second.

Abstract Author(s): Kristen Grauman, Trevor Darrell, Louis-Philippe Morency<br />Vision Interface Group<br />MIT Artificial Intelligence Laboratory