A real-time algorithm to detect eye blinks in a video sequence from a standard camera is proposed. Recent landmark detectors, trained on in-the-wild datasets exhibit excellent robustness against face resolution, varying illumination and facial expressions. We show that the landmarks are detected precisely enough to reliably estimate the level of the eye openness. The proposed algorithm therefor...

State-of-the-art algorithms offer a real-time human face and eye detection which can be used to detect eye-blink. In this paper we present a feature descriptor. Gradient orientations and magnitudes are used to build the feature descriptor. We use the difference between samples of open and closed eyes. Gradient descriptors are further used to train the SVM. SVM can predict the open or closed eye...

A Human-Computer Interaction (HCI) framework that is de-marked for people with serious inabilities to recreate control of a conventional machine mouse is presented. The cam based framework, screens a client's eyes and permits the client to simulate clicking the mouse utilizing deliberate blinks and winks. For clients who can control head developments and can wink with one eye while keeping thei...

As field of signal processing is widening in various security and surveillance applications, motivated the interest for implementing better application with less complications. A non-intrusive machine vision based concepts is used to simulate Drowsiness Detection System. The system is consisting of web camera which placed in a way that it records driver’s head movements in order to detect drows...

This work is motivated by our goal of providing non-contact head and eye based control of computer systems for people with motor difficulties. The system described here uses spatio-temporal filtering and variance maps to locate the head and find the eye-feature points respectively. These feature points are accurately tracked in the succeeding frames by using a modified version of the Lucas-Kana...

Blink detection plays an important role in many human-computer interaction applications for consumers. Unfortunately, deep neural network-based blink methods are not only susceptible to poor lighting conditions, but also the learning model is prone bias due imbalance dataset distribution. To solve these problems, we propose Estimation with Domain Adversarial Training (BEAT) network, which robus...

The blink reflex is modulated if a weak lead stimulus precedes the blink-eliciting stimulus. In two experiments, we examined the effects of the sensory modality of the lead and blink-eliciting stimuli on blink modulation. Acoustic, visual, or tactile lead stimuli were followed by an acoustic (Experiment 1) or an electrotactile (Experiment 2) blink-eliciting stimulus at lead intervals of -30, 0,...

Electroencephalogram (EEG) is easily contaminated by unwanted physiological artifacts, among which electrooculogram (EOG) artifacts due to eye blinking are known to be most dominant. The eye blink artifacts are reported to affect theta and alpha rhythms of frontal EEG signals, and hard to be accurately detected in an unsupervised way due to large individual variability. In this study, we propos...

Neural correlates of eye blink in healthy human subjects can be investigated using functional magnetic resonance imaging. However, the focus of most previous studies has been on intentional eye blinking. The goal of the present study was to examine the neural correlates of spontaneous eye blinking with the help of EOG measurements during data acquisition of fMRI. After the removal of the pulse ...

Eye blinking is one of the most frequent human actions. The control of blinking is thought to reflect complex interactions between maintaining clear and healthy vision and influences tied to central dopaminergic functions including cognitive states, psychological factors, and medical conditions. The most imminent consequence of blinking is a temporary loss of vision. Minimizing this loss of inf...