Blink detection for real-time eye tracking

Authors:
T. Morris;P. Blenkhorn;Farhan Zaidi
Affiliations:
Department of Computation, UMIST, Manchester M60 IQD, UK;Department of Computation, UMIST, Manchester M60 IQD, UK;Department of Computation, UMIST, Manchester M60 IQD, UK
Venue:
Journal of Network and Computer Applications
Year:
2002

Citing 3
Cited 12

Feature extraction from faces using deformable templates

International Journal of Computer Vision
Interactive-time vision: face recognition as a visual behavior

Interactive-time vision: face recognition as a visual behavior
Dual-State Parametric Eye Tracking

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000

Facial feature tracking for cursor control

Journal of Network and Computer Applications
Detecting eye blink states by tracking iris and eyelids

Pattern Recognition Letters
Simultaneous eye tracking and blink detection with interactive particle filters

EURASIP Journal on Advances in Signal Processing
Hands-free vision-based interface for computer accessibility

Journal of Network and Computer Applications
An adaptive blink detector to initialize and update a view-basedremote eye gaze tracking system in a natural scenario

Pattern Recognition Letters
Robust real time eye tracking for computer interface for disabled people

Computer Methods and Programs in Biomedicine
Automatic Method for Measuring Eye Blinks Using Split-Interlaced Images

Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends
An eye localization, tracking and blink pattern recognition system: Algorithm and evaluation

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A new low-cost eye tracking and blink detection approach: extracting eye features with blob extraction

ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Text composing software for disabled people, using blink and motion detection

ICCHP'10 Proceedings of the 12th international conference on Computers helping people with special needs
Your reactions suggest you liked the movie: automatic content rating via reaction sensing

Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Automatic classification of eye blink types using a frame-splitting method

EPCE'13 Proceedings of the 10th international conference on Engineering Psychology and Cognitive Ergonomics: understanding human cognition - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

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-Kanade tracking algorithm with pyramidal implementation. Accurate head and eye tracking results are obtained at a processing rate of more than 30 frames per second (fps) in more than 90% cases with a low false positive blink detection rate of 0.01%. This is achieved under varying lighting conditions for people of different ethnicity, with and without wearing glasses.