Face Detection Approach in Neural Network Based Method for Video Surveillance

Neural networks are adaptive information processing systems that offer attractive solutions for video surveillance. This application aims at identifying particular patterns. Also, MPEG-4 standard profiling strategy in facial animation guarantees that the standard can provide adequate solutions for video surveillance. The main goal of this presentation is to provide face detection for video surveillance using neural network based method. After providing the corresponding architecture for face detection, the emphasize is on the detector which is trained with multilayer back propagation neural networks. Three different face representations are taken into account, i.e. pixel representation, partial profile representation and eigenface representation. Based on this, three independent sub-detectors are generated. The detection rates are measured. The circle at about 94 % indicates the position where the neural network achieves the optimal performance.