Visual computing covers a range of disciplines within computer science such as computer graphics, image processing, visualisation, computer vision, and virtual or augmented reality. Our research develops and uses techniques across all of these and more, but most of our work falls into three main themes: Using visual input to make models of the world; Understanding images and the models we build from them using tools from machine learning; Visualising data in the context of the world around us; and Allowing people to interact with data and information in new ways.
Visualisation can be described as the process of converting abstract data into a visual representation that is comprehensible by a human observer, or in other words: making something visible. In our research, we look in particular into how to visualise information in Augmented Reality but also more general in 3D. More...
Capturing for XR
We are interested in exploring novel ways that allow users to capture their surroundings for replay in Virtual and Augmented Reality environments. In particular, we are looking into new ways how to capture such data without specialized hardware in a more casual way. More...
Images provide a rich source of information about the world, but each image only provides a partial view. By understanding the process of image formation, and combining information from multiple images, we can build up more detailed models of the world. This includes recovering 3D structure, analysing motion and changes over time, and modelling variations in the shape and appearance of objects. More...
Geometric models of the world are very useful, but they often lack the semantic information required for specific applications.
Techniques from machine learning allow us to augment images or models of the world to provide the ability to understand what we are seeing.