John T. Kelso

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We present DIVERSE, a highly modular collection of complimentary software packages designed to facilitate the creation of device independent virtual environments. DIVERSE is free/open source software, containing both end-user programs and C++ APIs (Application Programming Interfaces). DgiPf is the DIVERSE graphics interface to OpenGL Performer™. A program(More)
Traditional user interface evaluation usually is conducted in a laboratory where users are observed directly by evaluators. However, the remote and distributed location of users on the network precludes the opportunity for direct observation in usability testing. Further, the network itself and the remote work setting have become intrinsic parts of usage(More)
This paper describes a set of tools for performing measurements of objects in a virtual reality based immersive visualization environment. These tools enable the use of the immersive environment as an instrument for extracting quantitative information from data representations that hitherto had be used solely for qualitative examination. We provide, within(More)
In this paper we describe a flexible environment that combines scientific data mining with parallel computing in an immersive visualization environment. The goal is to minimize the time between the generation of a scientific hypothesis and the test of that idea, or science at the speed of thought.
We describe a method for calibrating an electromagnetic motion tracking device. Algorithms for correcting both location and orientation data are presented. In particular we use a method for interpolating rotation corrections that has not previously been used in this context. This method, unlike previous methods, is rooted in the geometry of the space of(More)
In order to move away from the current prescriptive design methods towards performance based methods for the design of structures under fire, we need validated computer models. The next section describes our approach for modeling and analysis.
This is the third in a series of articles that describe, through examples, how the Scientific Applications and Visualization Group (SAVG) at NIST has utilized high performance parallel computing, visualization, and machine learning to accelerate scientific discovery. In this article we focus on the use of high performance computing and visualization for(More)
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