IQ-station: A low cost portable immersive environment

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Abstract

The emergence of inexpensive 3D-TVs, affordable input and rendering hardware and open-source software has created a yeasty atmosphere for the development of low-cost immersive systems. A low cost system (here dubbed an IQ-station), fashioned from commercial off-the-shelf technology (COTS), coupled with targeted immersive applications can be a viable laboratory instrument for enhancing scientific workflow for exploration and analysis. The use of an IQ-station in a laboratory setting also has the potential of quickening the adoption of a more sophisticated immersive environment as a critical enabler in modern scientific and engineering workflows. Prior work in immersive environments generally required special purpose display systems, such as a head mounted display (HMD) or a large projector-based implementation, which have limitations in terms of cost, usability, or space requirements. The alternative platform presented here effectively addresses those limitations. This work brings together the needed hardware and software components to create a fully integrated immersive display and interface system that can be readily deployed in laboratories and common workspaces. By doing so, it is now feasible for immersive technologies to be included in researchers' day-to-day workflows. The IQ-station sets the stage for much wider adoption of immersive interfaces outside the small communities of virtual reality centers. In spite of this technical progress, the long-term success of these systems depends on resolving several important issues related to users and support. Key among these issues are: to what degree should hardware and software be customized; what applications and content are available; and how can a community be developed? © 2010 Springer-Verlag.

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Sherman, W. R., O’Leary, P., Whiting, E. T., Grover, S., & Wernert, E. A. (2010). IQ-station: A low cost portable immersive environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6454 LNCS, pp. 361–372). https://doi.org/10.1007/978-3-642-17274-8_36

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