Title :
Face Detecting Using Artificial Neural Network Approach
Author :
Nazeer, Shahrin Azuan ; Omar, Nazaruddin ; Jumari, Khairol Faisal ; Khalid, Marzuki
Author_Institution :
Telekom Res. & Dev. Sdn Bhd, UPM-MTDC, Serdang
Abstract :
A frontal face detection system using artificial neural network is presented. The system used integral image for image representation which allows fast computation of the features used. The system also applies the AdaBoost learning algorithm to select a small number of critical visual features from a very large set of potential features. Besides that, it also used cascade of classifiers algorithm which allows background regions of the image to be quickly discarded while spending more computation on promising face-like regions. Furthermore, a set of experiments in the domain of face detection is presented. The system yields a promising face detection performance
Keywords :
face recognition; image classification; image representation; learning (artificial intelligence); neural nets; AdaBoost learning; artificial neural network; frontal face detection system; image classification; image representation; Artificial intelligence; Artificial neural networks; Data acquisition; Electronic mail; Face detection; Facial features; Image representation; Intelligent robots; Layout; Poles and towers;
Conference_Titel :
Modelling & Simulation, 2007. AMS '07. First Asia International Conference on
Conference_Location :
Phuket
Print_ISBN :
0-7695-2845-7
DOI :
10.1109/AMS.2007.38