Machine Learning (Postgraduate/Undergraduate)
The aim of the module is to give students an understanding of machine learning methods, including pattern recognition, clustering and neural networks, and to allow them to apply such methods in a range of areas.
Machine Learning for Visual Data Analysis (Postgraduate/Undergraduate)
The module will cover the following topics: The Discrete Fourier Transform and the frequency content of images. The design and use of Gabor filters. Principal Component Analysis for denoising and compression. Unsupervised classification via feature space clustering. Texture segmentation with Gabor filters.
My research experience lies mainly in the areas of Computer Vision, Image Processing and Pattern Recognition, and their applications in Multimedia Analysis, Visual Communications and Multimodal Man Machine Interaction. My recent research focuses on Human Sensining and Facial And Body Gesture Analysis, Tracking and Recognition.
Keywords: Face and Gesture Recognition, Tracking, Facial (Expression) Analysis, Human Motion Recognition, Behaviour Analysis, Human Sensing, EEG Analysis, Multimedia Indexing.