Abstract
Facial expression is an important feature that gives information about a person's psychological situation. People use these expressions while communicating and socializing and they have lots of information related to inner world of an individual. Therefore it is important to understand the meaning of these facial expressions automatically and use this information. This paper presents a method for facial expression classification with grayscale images from Kaggle Face Dataset with a Convolutional Neural Network and a realtime user interface in order to test the performance online. Data augmentation is used to increase the diversity of the samples. Neural network is created with Matlab and user interface is created via App Designer. Different training and fine-tuning techniques are employed in the design. The overall accuracy 61.8% is achieved across seven different facial expression categories with test dataset supplied in Kaggle domain.
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