Recognizing Action Units for Facial Expression Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Blink detection for real-time eye tracking
Journal of Network and Computer Applications
Eye-State Action Unit Detection by Gabor Wavelets
ICMI '00 Proceedings of the Third International Conference on Advances in Multimodal Interfaces
Recognizing action units for facial expression analysis
Multimodal interface for human-machine communication
A real-time head nod and shake detector
Proceedings of the 2001 workshop on Perceptive user interfaces
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Parametric models for facial features segmentation
Signal Processing
Detecting eye blink states by tracking iris and eyelids
Pattern Recognition Letters
Robust measurement of ocular torsion using iterative Lucas-Kanade
Computer Methods and Programs in Biomedicine
Hierarchical Eyelid and Face Tracking
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Overview of automatic facial expressions analysis
VIIP '07 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing
Algorithm optimizations for low-complexity eye tracking
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Deterministic and stochastic methods for gaze tracking in real-time
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Tracking Iris contour with a 3D eye-model for gaze estimation
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Eye/eyes tracking based on a unified deformable template and particle filtering
Pattern Recognition Letters
Conic-based algorithm for visual line estimation from one image
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Facial feature tracking for emotional dynamic analysis
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
A robust and efficient algorithm for eye detection on gray intensity face
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Combined head, lips, eyebrows, and eyelids tracking using adaptive appearance models
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Estimating the visual direction with two-circle algorithm
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Toward exploiting location-based and video information in negotiated access control policies
ICISS'05 Proceedings of the First international conference on Information Systems Security
Recognizing facial expressions using a novel shape motion descriptor
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
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Most eye trackers work well for open eyes. However, blinking is a physiological necessity for humans. Moreover, for applications such as facial expression analysis and driver awareness systems, we need to do more than tracking the locations of the person's eyes but obtain their detailed description. We need to recover the state of the eyes (i.e. whether they are open or closed), and the parameters of an eye model (e.g. the location and radius of the iris, and the corners and height of the eye opening). In this paper, we develop a dual-state model based system of tracking eye features that uses convergent tracking techniques and show how it can be used to detect whether the eyes are open or closed, and to recover the parameters of the eye model. Processing speed on a Pentium II 400MHZ PC is approximately 3 frames/second. In experimental tests on 500 image sequences from child and adult subjects with varying colors of skin and eye, accurate tracking results are obtained in 98% of image sequences.