Human face, the most active and healthy part of human body and Eyes are one of the most complex features of it. It may be used to reduce some of their critical life complexities. Eye blinking is one of the prominent areas to solve many real world problems. The process of blink detection consists of two phases. These are eye tracking followed by detection of blink. The work that has been carried...

Introduction “Blink” is defined as closing and opening of the eyes in a small duration of time. In this study, we aimed to introduce a fast, robust, vision-based approach for blink detection. Materials and Methods This approach consists of two steps. In the first step, the subject’s face is localized every second and with the first blink, the system detects the eye’s location and creates an ope...

In this article, we develop a real-time mobile phone-based gaze tracking and eye-blink detection system on Android platform. Our eye-blink detection scheme is developed based on the time difference between two open eye states. We develop our system by finding the greatest circle—pupil of an eye. So we combine the both Haar classifier and Normalized Summation of Square of Difference template-mat...

Generally, blinks are treated on equal with artifacts and noise while analyzing EEG signals. However, blinks carry important information about mental processes and thus it is important to detect blinks accurately. The aim of the presented study is to propose a blink detection method and discuss its application for extracting blink rate variability, a novel concept that might shed some light on ...

Ocular artifact, namely eye-blink is an inevitable and one of the most destructive noises EEG signals. Many solutions detecting artifact were proposed. Different subsets features Machine Learning (ML) classifiers used for this purpose. But no comprehensive comparison these ML was presented. This paper presents twelve five classifiers, commonly in existing studies detection artifacts. An dataset...

In this paper we investigated how statistical properties of the blink rate variability changes during two mental tasks: reading a passage and memory testing. To construct time series of inter-blink intervals (blink rate variability) we detected exact blink time in EEG recordings using our blink detection algorithm. We found that among 13 subjects, all subjects blinked less during reading sessio...

Blinking is a spontaneous or voluntary action of human eyes. It has long been used for human-machine communication and human physiological detection. In these applications, detecting the eye’s states, opened or closed, is an important step and affects the accuracy of detecting human intention or physiological states. In this paper, we present a robust method to detect eye blink based on the int...

Nowadays, people spend more time in front of electronic screens like computers, laptops, TV screens, mobile phones or tablets which cause eye blink frequency to decrease. Each blink spreads the tears on the eye cornea to moisture and disinfect the eye. Reduced blink rate causes eye redness and dryness also known as Dry Eye, which belongs to the major symptoms of the Computer Vision Syndrome. Th...

The eyes are tracked and correlation scores between the actual eye and the corresponding “closed-eye” template are used to detect blinks. However, it requires offline training for different depths from the camera for the computation of the distance. In addition, the system requires initialization in which an Eye blinking is one of the prominent areas to solve many real world problems. The proce...

There has been a growing interest in the field of facial expression recognition especially in the last two decades. An example of such a system is the improvement of driver carefulness and accident reduction. The driver’s face is tracked while he is driving and he is warned if there seems to be an alerting fact that can result in an accident such as sleepy eyes, or looking out of the road. Furt...