Cognitive Vision Research Roadmap - David Vernon

Cognitive Vision Research RoadmapECVision - IST-2001-35454offers a rich repertoire of learning methods for such tasks. As a prominent example,concept learning using the version space method in the framework of logic-basedknowledge representation is one well-established methodology [Mitchell 97].In the last ten years, however, learning in a probabilistic framework has gainedincreasing importance due to the introduction of Bayesian Nets (in AI also known asbelief nets). Bayesian Nets provide a sound basis for evidential reasoning which maybe applied to diverse subtasks in vision. Moreover, recent work on combining logicbasedand probabilistic approaches, for example the work of Koller on Bayes Nets inconnection with relational structures [Getoor et al. 01], indicate that the gap betweenthe quantitative world of classical Computer Vision and the symbolic world ofclassical AI is rapidly closing.One of the research goals of Cognitive Vision is to be able to interpret scenes in termsof intended actions or plans, to ascribe intentions to agents, and to infer goals. This isclosely related, of course, to planning, one of the oldest and best established subareasof AI, for a representative collection see [Allen et al. 90]. Research on planning in AIalso includes plan recognition, for a probabilistic approach see [Charniak andGoldman 91], for multi-agent aspects see [Huber and Durfee 95]. Hence there is arich body of methods to build on. In addition, however, the vision task of interpretingobservations as intended actions also requires a deeper understanding of causality atthe physical level. When can one conclude that two occurrences are causal? Forrecent AI research into this topic see [Pearl 00].In summary, it is fair to say that AI, in particular common-sense reasoning, andvision, although early recognized to belong together, have not yet been integrated to asignificant extent. The main reason seems to be that Computer Vision and AI havegone separate ways in order to obtain sufficient maturity in their own respectivedisciplines before attempting an integration. But given the substantial relevant workoutlined above, time has definitely come to establish Cognitive Vision as a researchprogram which brings the two together.8