The computational perception of scene dynamics
Computer Vision and Image Understanding - Special issue on physics-based modeling and reasoning in computer vision
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Steps toward a cognitive vision system
AI Magazine
A knowledge-level approach for effective acting, sensing, and planning
A knowledge-level approach for effective acting, sensing, and planning
Computational Geometry: Algorithms and Applications
Computational Geometry: Algorithms and Applications
From images to bodies: modelling and exploiting spatial occlusion and motion parallax
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Reasoning about Movement in Two-Dimensions
Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
Formalising the Fisherman's Folly puzzle
Artificial Intelligence
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Reasoning about perception of depth and about spatial relations between moving physical objects is a challenging problem. We investigate the representation of depth and motion by means of depth profiles whereby each object in the world is represented as a single peak. We propose a logical theory, formulated in the situation calculus (SC), that is used for reasoning about object motion (including motion of the observer). The theory proposed here is comprehensive enough to accommodate reasoning about both sensor data and actions in the world. We show that reasoning about depth profiles is sound and complete with respect to actual motion in the world. This shows that in the conceptual neighbourhood diagram (CND) of all possible depth perceptions, the transitions between perceptions are logical consequences of the proposed theory of depth and motion.