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Declarative Reasoning about Space and Motion with Video

dc.contributor.authorSuchan, Jakob
dc.date.accessioned2018-01-08T08:13:27Z
dc.date.available2018-01-08T08:13:27Z
dc.date.issued2017
dc.description.abstractWe present a commonsense theory of space and motion for representing and reasoning about motion patterns in video data, to perform declarative (deep) semantic interpretation of visuo-spatial sensor data, e.g., coming from object tracking, eye tracking data, movement trajectories. The theory has been implemented within constraint logic programming to support integration into large scale AI projects. The theory is domain independent and has been applied in a range of domains, in which the capability to semantically interpret motion in visuo-spatial data is central. In this paper, we demonstrate its capabilities in the context of cognitive film studies for analysing visual perception of spectators by integrating the visual structure of a scene and spectators gaze acquired from eye tracking experiments.
dc.identifier.pissn1610-1987
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/11076
dc.publisherSpringer
dc.relation.ispartofKI - Künstliche Intelligenz: Vol. 31, No. 4
dc.relation.ispartofseriesKI - Künstliche Intelligenz
dc.subjectCognitive vision
dc.subjectSemantic interpretation of video
dc.subjectSpatio-temporal dynamics
dc.titleDeclarative Reasoning about Space and Motion with Video
dc.typeText/Journal Article
gi.citation.endPage330
gi.citation.startPage321

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