Computer Vision, Graphics, and Image Processing
Making large-scale support vector machine learning practical
Advances in kernel methods
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Automatic Eyeglasses Removal from Face Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
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In this paper we propose a method to verify the existence of eyeglasses in the frontal face images by support vector machine. The difficulty of such task comes from the unpredictable illumination and the complex composition of facial appearance and eyeglasses. The lighting uncertainty is eliminated by feature selection, where the orientation and anisotropic measure is chosen as the feature space. Due to the nonlinear composition of glasses to face and the small quantity of examples, support vector machine(SVM) is utilized to give a nonlinear decision surface. By carefully choosing kernel functions, an optimal classifier is achieved from training. The experiments illustrate that our model performs well in eyeglasses verification.