Prof. A G Cohn School of Computing University of Leeds |
Brief Biography
Tony Cohn holds a Personal Chair at the University of Leeds, where he is Professor of Automated Reasoning. He is presently Director of the Institute for Artificial Intelligence and Biological Systems. He leads a research group working on Knowledge Representation and Reasoning with a particular focus on qualitative spatial/spatio-temporal reasoning, the best known being the well cited Region Connection Calculus (RCC). His current research interests range from theoretical work on spatial calculi and spatial ontologies, to cognitive vision, modelling spatial information in the hippocampus, and detecting buried underground assets (e.g. utilities and archaeological residues) using a variety of geo-located sensors. He has been Chairman/President of SSAISB, ECCAI, KR inc, the IJCAI Board of Trustees and is presently Editor-in-Chief of the AAAI Press, Spatial Cognition and Computation, and the Artificial Intelligence journal. He was elected a founding Fellow of ECCAI, and is also a Fellow of AAAI, AISB, the BCS, and the IET.
Keynote Speech Title
Learning about Activities and Objects from Video
Keynote Speech Abstract
In this talk I will present ongoing work at Leeds on building models of video activity. I will present techniques, both supervised and unsupervised, for learning the spatio-temporal structure of tasks and events from video or other sensor data. In both cases, the representation will exploit qualititive spatio-temporal relations. A novel method for robustly transforming video data to qualitative relations will be presented. For supervised learning I will show how the supervisory burden can be reduced using what we term "deictic supervision", whilst in the unsupervised case I will present a method for learning the most likely interpretation of the training data. I will also show how objects can be "functionally categorised" according to their spatio-temporal behaviour and how the use of type information can help in the learning process, especially in the presence of noise. I will present results from several domains including a kitchen scenario and an aircraft apron.