Human eye closeness detection has gained wide applications in human computer interface designation, facial expression recognition, driver fatigue detection, and so on. In this work, we present an extensive comparison on several state of art appearance-based eye closeness detection methods, with emphasize on the role played by each crucial component, including geometric normalization, feature ex...

Human eye closeness detection has gained wide applications in human computer interface designation, facial expression recognition, driver fatigue detection, and so on. In this work, we present an extensive comparison on several state of art appearance-based eye closeness detection methods, with emphasize on the role played by each crucial component, including geometric normalization, feature ex...

Fatigue and driver drowsiness monitoring is an important subject for designing driver assistance systems. The measurement of eye closure is a fundamental step for driver awareness detection. We propose a method which is based on eyelid detection and the measurement of the distance between the eyelids. First, the face and the eyes of the driver are localized. After extracting the eye region, the...

The driver felt sleepy when they don’t take proper rest while driving on long routes. restless careless mistake could be fatal to as well others’ lives. This issue has been increased such a level that system required avoid accidents and save life. alertness detection can play significant role hazards. identify the drowsiness face of generate an alarm for them stop or necessary actions. Eye stat...

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...

Maximum and minimum computed across channels is used to monitor the Electroencephalogram signals for possible change of the eye state. Upon detection of a possible change, the last two seconds of the signal is passed through Multivariate Empirical Mode Decomposition and relevant features are extracted. The features are then fed into Logistic Regression and Artificial Neural Network classifiers ...

Real-time, accurate, and robust pupil detection is an essential prerequisite for pervasive video-based eye-tracking. However, automated pupil detection in realworld scenarios has proven to be an intricate challenge due to fast illumination changes, pupil occlusion, non-centered and off-axis eye recording, as well as physiological eye characteristics. In this paper, we approach this challenge th...

Accurate classification of eye state is a prerequisite for preventing automobile accidents due to driver drowsiness. Previous methods of classification, based on features extracted for a single eye, are vulnerable to eye localization errors and visual obstructions, and most use a fixed threshold for classification, irrespective of variations in the driver’s eye shape and texture. To address the...

This paper presents an efficient approach to achieve fast and accurate eye states detection in still gray level images with unconstrained background. The structure of eye region is used as a robust cue to find eye pair candidates. Eyes are located by eye verification using SVMs. The eye contour information is used to detect whether eyes are open or closed after locating eyes. The proposed metho...