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  • Author or Editor: Balázs Tukora x
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A very special artistic event can be held with the “virtual” sculpture exhibition. Cellular phones can be used in this project to show the public square as if a non-existing sculpture has been located on it. However, the idea of amplifying the environment with virtual objects is not a new concept, the limited performance of the used visualizing devices requires developing faster and more effective algorithms for this purpose. This paper discusses the arising problems during the development of this algorithm and gives proposals for solving them.

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Abstract:

Numerous volume rendering techniques are available to display 3D datasets on desktop computers and virtual reality devices. Recently the spreading of mobile and standalone virtual reality headsets has brought the need for volume visualization on these platforms too. However, the volume rendering techniques that show good performance in desktop environment underachieve on these devices, due to the special hardware conditions and visualization requirements. To speed up the volumetric rendering to an accessible level a hybrid technique is introduced, a mix of the ray casting and 3D texture mapping methods. This technique increases 2-4 times the frame rate of displaying volumetric data on mobile and standalone virtual reality headsets as compared to the original methods. The new technique was created primarily to display medical images but it is not limited only to this type of volumetric data.

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The evolution of GPUs (graphics processing units) has been enormous in the past few years. Their calculation power has improved exponentially, while the range of the tasks computable on GPUs has got significantly wider. The milestone of GPU development of the recent years is the appearance of the unified architecture-based devices. These GPUs implement a massively parallel design, which led them be capable not only of processing the common computer graphics tasks, but qualifies them for performing highly parallel mathematical algorithms effectively. Recognizing this availability GPU providers have issued developer platforms, which let the programmers manage computations on the GPU as a data-parallel computing device without the need of mapping them to a graphics API. Researchers salute this initiative, and the application of the new technology is quickly spreading in various branches of science

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