Abstract
A new technique to detect eye blinks is proposed based on automatic tracking of facial landmarks to localise the eyes and eyelid contours. Automatic facial landmarks detectors are trained on an in-the-wild dataset and shows an outstanding robustness to varying lighting conditions, facial expressions, and head orientation. The proposed technique estimates the facial landmark positions and extracts the vertical distance between eyelids for each video frame. Next, a Savitzky–Golay (SG) filter is employed to smooth the obtained signal while keeping the peak information to detect eye blinks. Finally, eye blinks are detected as sharp peaks and a finite state machine is used to check for false blink and true blink cases based on their duration. The efficiency of the proposed technique is shown to outperform the state-of-the-art methods on three standard datasets.
Highlights
Blink detection technology has been applied in various fields such as the interaction between disabled people and computers [1], drowsiness detection [2], and cognitive load [3]
An finite state machine (FSM) is used to find true blink cases according to the blink duration
ZFace is used to track 49 facial landmarks from videos, where eye features are detected for each video frame, and the eye-opening state is estimated using the vertical distance (d) between eyelids
Summary
Blink detection technology has been applied in various fields such as the interaction between disabled people and computers [1], drowsiness detection [2], and cognitive load [3]. Other methods use template matching, where templates with open and/or closed eyes are learned and a normalised cross correlation coefficient is computed for an eye region of each image [7]. These methods, are sensitive to image resolution, illumination, and facial movement dynamics. The eye openness state is characterised by measuring the distance between eyelids. This is followed by applying Savitzky–Golay (SG) filtering to smooth the obtained signal and reduce signal noise. An FSM is used to find true blink cases according to the blink duration
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