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GPU-Based Hierarchical Computations for View Independent Visibility

Rhushabh Goradia, Prekshu Ajmera, Sharat Chandran
ViGIL, Department of Computer Science and Engineering, Indian Institute of Technology Bombay, Mumbai
Sixth Indian Conference on Computer Vision, Graphics & Image Processing, 2008. ICVGIP ’08

@inproceedings{goradia2008gpu,

   title={GPU-based hierarchical computations for view independent visibility},

   author={Goradia, R. and Ajmera, P. and Chandran, S.},

   booktitle={Computer Vision, Graphics & Image Processing, 2008. ICVGIP’08. Sixth Indian Conference on},

   pages={560–567},

   year={2008},

   organization={IEEE}

}

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With rapid improvements in the performance and programmability, graphics processing units (GPUs) have fostered considerable interest in substantially reducing the running time of compute intensive problems. The solution to the view-independent mutual point-pair visibility problem (required for inter-reflections in global illumination) can, it would seem, require the capabilities of the GPUs. In this paper, various ways of parallelizing the construction of the visibility map (V-map, a description of mutual visibility) are presented to lead the way for an implementation that achieves a speedup of 11 or more. We evaluate our scheme qualitatively and quantitatively, and conclude that parallelizing the V-map construction algorithm is eminently useful.
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