1)local Feature Representations for Facial Expression Recognition Based on Differences of Gray Color Values of Neighboring Pixels
چکیده
Title of Dissertation Local Feature Representations for Facial Expression Recognition Based on Differences of Gray Color Values of Neighboring Pixels Author Mohammad Shahidul Islam Degree Doctor of Philosophy (Computer Science and Information Systems) Year 2013 A fruitful way for creating any innovative system in a computing environment is to integrate a sufficiently user-friendly interface with the ordinary end user. Successful design of such a user-friendly interface, however, means more than just the ergonomics of the panels and displays. It also requires that engineers precisely define what information to use and how, where, and when to use it. Facial expression as a natural, non-intrusive and efficient way of communication has been considered as one of the possible inputs of such interfaces. The research interest in facial expression recognition has grown due to its potential applications. Many local feature representations such as Gabor filters, LBP had been proposed for facial expression recognition. However, accuracy rates and running time of facial expression recognition achieved by these representations have yet to be improved. The work of this thesis aims at designing a robust and effective Facial Expression Recognition (FER) system that uses simple but effective gray scale invariant local descriptors for face expression recognition. The local feature pattern at a pixel is computed based on differences of gray color values of its neighboring pixels. The pattern represents the changes of gray color values of pixels in its surrounding area. Four alternative local feature representations are proposed depending on the numbers of considered directions and neighboring pixels. To create the feature vector for an image, the facial image is divided into blocks and the histograms counting the occurrences of all