Active shape models—their training and application
Computer Vision and Image Understanding
Laplacian Eigenmaps for dimensionality reduction and data representation
Neural Computation
Appearance-based Eye Gaze Estimation
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Online Learning of Probabilistic Appearance Manifolds for Video-Based Recognition and Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Learning Appearance Manifolds from Video
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Unsupervised Learning of Image Manifolds by Semidefinite Programming
International Journal of Computer Vision
Sparse and Semi-supervised Visual Mapping with the S^3GP
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Description of interest regions with local binary patterns
Pattern Recognition
Estimating the eye gaze from one eye
Computer Vision and Image Understanding - Special issue on eye detection and tracking
In the Eye of the Beholder: A Survey of Models for Eyes and Gaze
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel approach to 3-D gaze tracking using stereo cameras
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Inferring human gaze from appearance via adaptive linear regression
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Two of the challenges in appearance-based gaze tracking are: 1) prediction accuracy, 2) the efficiency of calibration process, which can be considered as the collection and analysis phase of labelled and unlabelled eye data. In this paper, we introduce an appearance-based gaze tracking model with a rapid calibration. First we propose to concatenate local eye appearance Center-Symmetric Local Binary Pattern(CS-LBP) descriptor for each subregion of eye image to form an eye appearance feature vector. The spectral clustering is then introduced to get the supervision information of eye manifolds on-line. Finally, taking advantage of eye manifold structure, a sparse semi-supervised Gaussian Process Regression(GPR) method is applied to estimate the subject's gaze coordinates. Experimental results demonstrate that our system with an efficient and accurate 5-points calibration not only can reduce the run-time cost but also can lead to a better accuracy result of 0.9°.