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88
COMM: Designing a well-founded multimedia ontology for the web
- In ISWC
, 2007
"... Abstract. Semantic descriptions of non-textual media available on the web can be used to facilitate retrieval and presentation of media assets and documents containing them. While technologies for multimedia semantic descriptions already exist, there is as yet no formal description of a high qualit ..."
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Cited by 75 (19 self)
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Abstract. Semantic descriptions of non-textual media available on the web can be used to facilitate retrieval and presentation of media assets and documents containing them. While technologies for multimedia semantic descriptions already exist, there is as yet no formal description of a high quality multimedia ontology that is compatible with existing (semantic) web technologies. We explain the complexity of the problem using an annotation scenario. We then derive a number of requirements for specifying a formal multimedia ontology before we present the developed ontology, COMM, and evaluate it with respect to our requirements. We provide an API for generating multimedia annotations that conform to COMM.
Understanding video events: A survey of methods for automatic interpretation of semantic occurrences in videos
- TSMC
"... Abstract: Understanding Video Events, the translation of low-level content in video sequences into highlevel semantic concepts, is a research topic that has received much interest in recent years. Important applications of this work include smart surveillance systems, semantic video database indexin ..."
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Cited by 51 (0 self)
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Abstract: Understanding Video Events, the translation of low-level content in video sequences into highlevel semantic concepts, is a research topic that has received much interest in recent years. Important applications of this work include smart surveillance systems, semantic video database indexing, and interactive systems. This technology can be applied to several video domains including: airport terminal, parking lot, traffic, subway stations, aerial surveillance, and sign language data. In this work we survey the two main components of the event understanding process: Abstraction and Event modeling. Abstraction is the process of molding the data into informative units to be used as input to the event model. Event modeling is devoted to describing events of interest formally and enabling recognition of these events as they occur in the video sequence. Event modeling can be further decomposed in the categories of Pattern Recognition Methods, State Event Models, and Semantic Event Models. In this survey we discuss this proposed taxonomy of the literature, offer a unifying terminology, and discuss popular abstraction schemes (e.g. Motion History Images) and event modeling formalisms (e.g. Hidden Markov Model) and their use in video event understanding using extensive examples from the literature. Finally we consider the application domain of video event understanding in light of the proposed taxonomy, and propose future directions for research in this field.
Ontology-based reasoning techniques for multimedia interpretation and retrieval
, 2007
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Scene Interpretation as a Configuration Task
- Künstliche Intelligenz, 3/2005, BöttcherIT Verlag, Bremen
, 2005
"... Abstract. From past research it is known that both knowledge-based scene interpretation and knowledge-based configuration can be conceived as logical model construction. In this report we show that also from an applicationoriented point of view, both tasks are very similar and existing configuration ..."
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Cited by 18 (11 self)
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Abstract. From past research it is known that both knowledge-based scene interpretation and knowledge-based configuration can be conceived as logical model construction. In this report we show that also from an applicationoriented point of view, both tasks are very similar and existing configuration technology can be used to implement a generic scene interpretation system with highly useful features, in particular expressive knowledge representation, flexible control, knowledge-guided hypothesis generation and constraint management. We describe an experiment where a table laying scene-inprogress is interpreted using the configuration system KONWERK as part of our scene interpretation system SCENIC. 1
Multimedia Interpretation for Dynamic Ontology Evolution
- JOURNAL OF LOGIC AND COMPUTATION, SPECIAL ISSUE ON ONTOLOGY DYNAMICS
, 2008
"... The recent success of distributed and dynamic infrastructures for knowledge sharing has raised the need for semiautomatic/automatic ontology evolution strategies. Ontology evolution is generally defined as the timely adaptation of an ontology to changing requirements and the consistent propagation o ..."
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Cited by 16 (10 self)
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The recent success of distributed and dynamic infrastructures for knowledge sharing has raised the need for semiautomatic/automatic ontology evolution strategies. Ontology evolution is generally defined as the timely adaptation of an ontology to changing requirements and the consistent propagation of changes to dependent artifacts. In this article, we present an ontology evolution approach in the context of multimedia interpretation. Ontology evolution in this context relies on the results obtained through reasoning for the interpretation of multimedia resources, through population of the ontology with new individuals, or through enrichment of the ontology with new concepts and new semantic relations. The article analyses the results of interpretation, population and enrichment obtained in evaluation experiments in terms of measures such as precision and recall. The evaluation reveals encouraging results.
Multimedia Interpretation as Abduction
- In Proc. DL-2007: International Workshop on Description Logics
, 2007
"... Abstract. In this work we present an approach to interpret information extracted from multimedia documents through Abox abduction, which we consider as a new type of non-standard retrieval inference service in Description Logics (DLs). We discuss how abduction can be adopted to interpret multimedia ..."
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Cited by 15 (6 self)
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Abstract. In this work we present an approach to interpret information extracted from multimedia documents through Abox abduction, which we consider as a new type of non-standard retrieval inference service in Description Logics (DLs). We discuss how abduction can be adopted to interpret multimedia content through explanations. In particular, we present a framework to generate explanations, and introduce a preference measure for selecting ‘preferred ’ explanations. 1 1
M.: Symbol grounding for semantic image interpretation : from image data to semantics
- In: Proceedings of the Workshop on Semantic Knowledge in Computer Vision, ICCV
, 2005
"... This paper presents an original approach for the symbol grounding problem involved in semantic image interpretation, i.e. the problem of the mapping between image data and semantic data. Our approach involves the following aspects of cognitive vision: knowledge acquisition and knowledge representati ..."
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Cited by 13 (1 self)
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This paper presents an original approach for the symbol grounding problem involved in semantic image interpretation, i.e. the problem of the mapping between image data and semantic data. Our approach involves the following aspects of cognitive vision: knowledge acquisition and knowledge representation, reasoning and machine learning. The symbol grounding problem is considered as a problem as such and we propose an independent cognitive system dedicated to symbol grounding. This symbol grounding system introduces an intermediate layer between the semantic interpretation problem (reasoning in the semantic level) and the image processing problem. An important aspect of the work concerns the use of two ontologies to make easier the communication between the different layers: a visual
Combining perception and knowledge processing for everyday manipulation
- In IEEE/RSJ International Conference on Intelligent RObots and Systems
"... Abstract — This paper describes and discusses the ..."
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Formalizing Multimedia Interpretation based on Abduction over Description Logic Aboxes ⋆
"... Abstract. The paper describes how interpretations of multimedia documents can be formally derived using abduction over domain knowledge represented in an ontology. The approach uses an expressive ontology specification language, namely description logics in combination with logic programming rules, ..."
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Cited by 12 (1 self)
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Abstract. The paper describes how interpretations of multimedia documents can be formally derived using abduction over domain knowledge represented in an ontology. The approach uses an expressive ontology specification language, namely description logics in combination with logic programming rules, and formalizes the multimedia interpretation process using a combined abduction and deduction operation. We describe how the observables as well as the space of abducibles can be formally defined. The approach is evaluated using examples from text processing, but can also be applied to interpret content in other modalities. 1
Architectural Reconstruction of 3D Building Objects through Semantic Knowledge Management
- in 11th ACIS International Conference on Software Engineering Artificial Intelligence Networking and Parallel/Distributed Computing (SNPD), 2010
"... Abstract—This paper presents an ongoing research which aims at combining geometrical analysis of point clouds and semantic rules to detect 3D building objects. Firstly by applying a previous semantic formalization investigation, we propose a classification of related knowledge as definition, partial ..."
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Cited by 11 (7 self)
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Abstract—This paper presents an ongoing research which aims at combining geometrical analysis of point clouds and semantic rules to detect 3D building objects. Firstly by applying a previous semantic formalization investigation, we propose a classification of related knowledge as definition, partial knowledge and ambiguous knowledge to facilitate the understanding and design. Secondly an empirical implementation is conducted on a simplified building prototype complying with the IFC standard. The generation of empirical knowledge rules is revealed and semantic scopes are addressed both in the bottom up manner along the line of geometry � topology � semantic, and a vice versa top down manner. Concrete implementation is on the platform of protégé with Semantic Web Rule Language (SWRL). Keywords- semantic; knowledge management; formal; epistemology; cognition I.