Abstract:
This research focuses on developing a mobile communication assistant for the disabled utilizing the biometrics information recognition in real time. We utilized their face features for our recognition. Our disabled community includes the palsies and autistics that could not make comprehensible speech due to disabilities or difficulties. However they have facial expression ability and incomprehensible speech that can be interpreted for their needs or requests. Their facial expressions may not be identical at all times for a specific need. Furthermore, each disabled is unique and uses a different way of expressions. Thus the communication assistant requires artificial intelligence in our proposed system. After a thorough research in face recognition and artificial intelligence, neural network coupled with Gabor feature extraction is found to outperform others. A neural network with Gabor filters is built to train the facial expression classifiers. Through our testing and evaluation with the volunteers, it has helped them expressing their needs with 85% successful recognition rates.
Keywords: Emotion communication, Gabor feature extraction. View full Article