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Despite the wide amount of computer graphics frameworks and solutions available for virtual reality, it is still difficult to find a perfect one fitting at the same time the many constraints of research and educational contexts. Advanced functionalities and user-friendliness, rendering speed and portability, or scalability and image quality are opposite characteristics rarely found into a same approach. Furthermore, fruition of virtual reality specific devices like CAVEs or wearable systems is limited by their costs and accessibility, being most of these innovations reserved to institutions and specialists able to afford and manage them through strong background knowledge in programming. Finally, computer graphics and virtual reality are a complex and difficult matter to learn, due to the heterogeneity of notions a developer needs to practice with before attempting to implement a full virtual environment. In this thesis we describe our contributions to these topics, assembled in what we called the Mental Vision platform. Mental Vision is a framework composed of three main entities. First, a teaching/research oriented graphics engine, simplifying access to 2D/3D real-time rendering on mobile devices, personal computers and CAVE systems. Second, a series of pedagogical modules to introduce and practice computer graphics and virtual reality techniques. Third, two advanced VR systems: a wearable, lightweight and handsfree mixed reality setup, and a four sides CAVE designed through off the shelf hardware. In this dissertation we explain our conceptual, architectural and technical approach, pointing out how we managed to create a robust and coherent solution reducing complexity related to cross-platform and multi-device 3D rendering, and answering simultaneously to contradictory common needs of computer graphics and virtual reality for researchers and students. A series of case studies evaluates how Mental Vision concretely satisfies these needs and achieves its goals on in vitro benchmarks and in vivo scientific and educational projects.
Luciano Andres Abriata, Fabio Jose Cortes Rodriguez