A new eye blink detection algorithm is proposed. It is based on analyzing the variance of the vertical motions in the eye region. The face and eyes are detected with a Viola-Jones type algorithm. Next, a flock of KLT trackers is placed over the eye region. For each eye, region is divided into 3 × 3 cells. For each cell an average "cell" motion is calculated. Simple state machines analyse the variances for each eye. The proposed method has lower false positive rate compared to other methods based on tracking. We introduce a new challenging dataset Eyeblink8. Our method achieves the best reported mean accuracy 99 % on the Talking dataset and state-of-the-art results on the ZJU dataset.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.