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Perceptual Narratives of Space and Motion for Semantic Interpretation of Visual Data
[chapter]
2015
Lecture Notes in Computer Science
We propose a commonsense theory of space and motion for the high-level semantic interpretation of dynamic scenes. The theory provides primitives for commonsense representation and reasoning with qualitative spatial relations, depth profiles, and spatio-temporal change; these may be combined with probabilistic methods for modelling and hypothesising event and object relations. The proposed framework has been implemented as a general activity abstraction and reasoning engine, which we demonstrate
doi:10.1007/978-3-319-16181-5_24
fatcat:gcrh3sjjtzdavllpcscf4hnydm