A hierarchical neural network for human face detection

This paper summarizes a research effort in human face detection. A system to locate human faces in images, especially when used as a front-end for a human face identification system, could have many applications in the law enforcement and security professions. The approach presented here is a hybrid system using an edge-enhancing preprocessor and four back-propagation neural networks arranged in a hierarchical structure. The method proposed successfully detected faces wearing glasses and all faces in images which contained multiple faces. The results obtained are reported along with a discussion for improving the system.

[1]  Ashok Samal,et al.  Artificial Neural Network architectures for human face detection , 1992 .

[2]  Ashok Samal,et al.  Automatic recognition and analysis of human faces and facial expressions: a survey , 1992, Pattern Recognit..

[3]  Terrence J. Sejnowski,et al.  SEXNET: A Neural Network Identifies Sex From Human Faces , 1990, NIPS.

[4]  Ian Craw,et al.  Automatic extraction of face-features , 1987, Pattern Recognit. Lett..

[5]  London,et al.  Light, Colour and Vision , 1969 .

[6]  Venu Govindaraju,et al.  Locating human faces in newspaper photographs , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.