Human eyes detection using hybrid neural method

In this paper, a novel hybrid neural method for human eyes detection is proposed. Firstly, the input facial image is preprocessed for normalization. Then, the candidates of eyes regions are detected based on a modified version of radial basis function (RBF) neural networks. Finally, a hierarchical knowledge-based approach is presented to validate these candidates and to locate the positions of both eyes. Our method has been tested on a database of facial images and achieves a good performance.

[1]  Thomas S. Huang,et al.  Human face detection in a complex background , 1994, Pattern Recognit..

[2]  Sun-Yuan Kung,et al.  Face recognition/detection by probabilistic decision-based neural network , 1997, IEEE Trans. Neural Networks.

[3]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[4]  Paul Juell,et al.  A hierarchical neural network for human face detection , 1996, Pattern Recognit..

[5]  Roberto Brunelli,et al.  Face Recognition: Features Versus Templates , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  A. Yuille Deformable Templates for Face Recognition , 1991, Journal of Cognitive Neuroscience.

[7]  Wei-Chung Lin,et al.  Extracting facial features by an inhibitory mechanism based on gradient distributions , 1996, Pattern Recognit..