5 May 2000 OpenSkies: a commercial 3D distributed visualization and simulation toolkit
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Proceedings Volume 3905, 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making; (2000) https://doi.org/10.1117/12.384872
Event: 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, 1999, Washington, DC, United States
Abstract
A growing need for more advanced training capabilities and the proliferation of government standards into the commercial market has inspired Cybernet to create an advanced, distributed 3D Simulation Toolkit. This system, called OpenSkies, is a truly open, realistic distributed system for 3D visualization and simulation. One of the main strengths of OpenSkies is its capability for data collection and analysis. Cybernet's Data Collection and Analysis Environment is closely integrated with OpenSkies to produce a unique, quantitative, performance-based measurement system. This system provides the capability for training students and operators on any complex equipment or system that can be created in a simulated world. OpenSkies is based on the military standard HLA networking architecture. This architecture allows thousands of users to interact in the same world across the Internet. Cybernet's OpenSkies simulation system brings the power and versatility of the OpenGL programming API to the simulation and gaming worlds. On top of this, Cybernet has developed an open architecture that allows the developer to produce almost any kind of new technique in their simulation. Overall, these capabilities deliver a versatile and comprehensive toolkit for simulation and distributed visualization.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Paul N. Cobb, Paul N. Cobb, Charles J. Jacobus, Charles J. Jacobus, Douglas Haanpaa, Douglas Haanpaa, } "OpenSkies: a commercial 3D distributed visualization and simulation toolkit", Proc. SPIE 3905, 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, (5 May 2000); doi: 10.1117/12.384872; https://doi.org/10.1117/12.384872
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