Current real-time VR applications are based on well-defined digital representations of the environment. In order to render a realistic looking environment with good performance, artists and developers with specific expertise are indispensable to create optimized data. However modern applications, especially those incorporating data from geo information (GIS) or product data management (PDM) systems, need to be able to use unrefined data without offline conversion or loss of render performance. In this paper we present an extensible object oriented graph database, which further embraces the paradigm of object orientation by incorporating the simulation functionality into the database itself. Whole scene descriptions including all functionalities can be described by one single database. Optimization techniques will be introduced, which are automatically applied to the simulation data, in order to extract a render-friendly structure. Specific semantic objects can be interpreted by the render framework to enhance the simulation, in both function and visual representation.
In this paper we present a new interdisciplinary approach to geographic information systems. The integration of object-oriented data modeling, 3D real-time simulation, virtual reality techniques and remote sensing methods with new semantic world modeling techniques and well known geo information system (GIS) functionalities provides the basis for a new class of “Virtual Testbeds”. These testbeds build on a new approach which combines state-of-the-art GIS functionalities to deal with complex and large geographical data sets with the intuitive operability and the advanced simulation capabilities of latest robotic and automation simulation components. Besides the simulation algorithms, the testbeds take advantage of advanced modeling capabilities to (semi) automatic ally generate models of “natural” environments in e.g. forests or cities. Based on remote sensing data, not only geometric shapes are derived, but also an object’s “function” or “semantics”. The new ideas have already been applied to various applications of which the most successful will also be described in this paper.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.