Integrating semantic directional relationships into virtual environments: a meta-modelling approach

  • Authors:

  • T.-H. Trinh;P. Chevaillier;M. Barange;J. Soler;P. De Loor;R. Querrec

  • Affiliations:

  • European University of Brittany, ENIB-UEB, LISYC, CERV, Plouzané, France;European University of Brittany, ENIB-UEB, LISYC, CERV, Plouzané, France;European University of Brittany, ENIB-UEB, LISYC, CERV, Plouzané, France;European University of Brittany, ENIB-UEB, LISYC, CERV, Plouzané, France;European University of Brittany, ENIB-UEB, LISYC, CERV, Plouzané, France;European University of Brittany, ENIB-UEB, LISYC, CERV, Plouzané, France

  • Venue:
  • EGVE - JVRC'11 Proceedings of the 17th Eurographics conference on Virtual Environments & Third Joint Virtual Reality
  • Year:
  • 2011

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Abstract

This study is concerned with semantic modelling of virtual environments (VEs). A semantic model of a VE provides an abstract and high level representation of main aspects of the environment: ontological structures, behaviours and interactions of entities, etc. Furthermore, such a semantic model can be explored by artificial agents to exhibit human-like behaviours or to assist users in the VE. Previous research focused on formalising a knowledge layer that is a conceptual representation of scene content or application's entities. However, there still lacks of a semantic representation of spatial knowledge. This paper proposes to integrate a semantic model of directional knowledge into VEs. Such a directional model allows to specify relationships such as "left", "right", "above" or "north", "south" that are critical in many applications of VEs (e.g., VEs for training, navigation aid systems). We focus particularly on modelling, computing, and visualising directional relationships. First, we propose a theoretical model of direction in VEs that enables the specification of direction both from a first- and third-person perspective. Second, we propose a generic architecture for modelling direction in VEs using a meta-modelling approach. Directional relationships are described in a qualitative manner and at a conceptual level, and thus are abstract from metrical details of VEs. Finally, we show how our semantic model of direction can be used in a cultural heritage application to specify behaviours of artificial agents and to visualise directional constraints.