Evaluation and Knowledge Representation Formalisms to Improve Video Understanding

Georis, B.; Mazière, Magali; Bromond, F.

doi:10.1109/icvs.2006.23

Cited by 6 publications

(4 citation statements)

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“…In his long-standing work on traffic scene interpretation [7,1,2], Nagel developed situation-graph trees, where hierarchically organized frame-based state descriptions of traffic situations are embedded in a state-transition structure. A similar structure was also realised by [3,4,8] in terms of scenarios for recognizing bank robberies or airport activities. Compositional and taxonomical hierarchies of structure-based configuration systems as a framework for flexible scene interpretation strategies realising both bottomup and top-down interpretation steps are proposed in [10].…”

Section: Introductionmentioning

confidence: 99%

Generation of Rules from Ontologies for High-Level Scene Interpretation

Bohlken

Neumann

2009

Lecture Notes in Computer Science

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Abstract. In this paper, a novel architecture for high-level scene interpretation is introduced, which is based on the generation of rules from an OWL-DL ontology. It is shown that the object-centered structure of the ontology can be transformed into a rule-based system in a native and systematic way. Furthermore the integration of constraints -which are essential for scene interpretation -is demonstrated with a temporal constraint net, and it is shown how parallel computing of alternatives can be realised. First results are given using examples of airport activities.

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Section: Introductionmentioning

confidence: 99%

Generation of Rules from Ontologies for High-Level Scene Interpretation

Bohlken

Neumann

2009

Lecture Notes in Computer Science

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“…These features are largely undisputed in the scene interpretation community [4,5,6], but a few remarks concerning the realization in SCENIC are in order. First, interpretation is not considered as a strictly symbolic process.…”

Section: Scene Interpretation In Etrimsmentioning

confidence: 99%

Learning and Recognizing Structures in Façade Scenes (eTRIMS)—A Retrospective

Hotz

Neumann

2010

Künstl Intell

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“…Compositional hierarchies have been employed for high-level scene interpretation by many researchers [1,2,3,4,5] with basically non-probabilistic (crisp) framebased representations, as commonly used in AI. Rimey [6] was the first to model compositional hierarchies with tree-shaped Bayesian Networks (BNs), requiring parts of an aggregate to be conditionally independent.…”

Section: Related Workmentioning

confidence: 99%