Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Eye detection by using fuzzy template matching and feature-parameter-based judgement
Pattern Recognition Letters
What's in the eyes for attentive input
Communications of the ACM
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel method for detecting lips, eyes and faces in real time
Real-Time Imaging - Special issue on spectral imaging
Driver State Monitor from DELPHI
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Toward a decision-theoretic framework for affect recognition and user assistance
International Journal of Human-Computer Studies - Human-computer interaction research in the managemant information systems discipline
A Real generalization of discrete AdaBoost
Artificial Intelligence
Fingerprint matching based on weighting method and the SVM
Neurocomputing
Multi-view face and eye detection using discriminant features
Computer Vision and Image Understanding
Sigma point Kalman filter for bearing only tracking
Signal Processing - Special section: Multimodal human-computer interfaces
A visual approach for driver inattention detection
Pattern Recognition
An improved likelihood model for eye tracking
Computer Vision and Image Understanding
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Simultaneous eye tracking and blink detection with interactive particle filters
EURASIP Journal on Advances in Signal Processing
A neural-based remote eye gaze tracker under natural head motion
Computer Methods and Programs in Biomedicine
Eye localization in low and standard definition content with application to face matching
Computer Vision and Image Understanding
Robust real time eye tracking for computer interface for disabled people
Computer Methods and Programs in Biomedicine
Automated eye tracking system calibration using artificial neural networks
Computer Methods and Programs in Biomedicine
A non-contact device for tracking gaze in a human computer interface
Computer Vision and Image Understanding - Special issue on eye detection and tracking
An embedded system for an eye-detection sensor
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Eye gaze tracking techniques for interactive applications
Computer Vision and Image Understanding - Special issue on eye detection and tracking
A novel non-intrusive eye gaze estimation using cross-ratio under large head motion
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Task oriented facial behavior recognition with selective sensing
Computer Vision and Image Understanding
On selection and combination of weak learners in AdaBoost
Pattern Recognition Letters
Feature selection for SVM via optimization of kernel polarization with Gaussian ARD kernels
Expert Systems with Applications: An International Journal
Eye/eyes tracking based on a unified deformable template and particle filtering
Pattern Recognition Letters
Automatic eye detection using intensity filtering and K-means clustering
Pattern Recognition Letters
AdaBoost-based face detection for embedded systems
Computer Vision and Image Understanding
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
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A novel approach to Robust real-time multi-user pupil detection and tracking is presented, and this kind of detection and tracking behaves well under the circumstance of various illumination or large-scale head motion. Firstly, with active IR illumination, the possible positions of human pupils are depicted according to bright pupil effect and then some image pretreatment is conducted to diminish the fake pupil positions. Secondly, other than detecting human pupils directly, human faces in the image would be detected with real AdaBoost and the detected face positions would be optimized in order to save the time of whole processing. Thirdly, based on the faces detected, human pupils would be detected with real support vector machine (real SVM) and correlation matching. At last, the human pupils detected would be tracked with Kalman forecast in order to save the detection time of next image. Results from a series of experiments show that the new method could achieve real-time (30 frame per second) with a success rate of 95% for multiple users, and it is also proved that the new method is robust for illumination variation and large-scale head motion.