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Rasterisation-based progressive photon mapping

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Abstract

Ray tracing on the GPU has been synergistically operating alongside rasterisation in interactive rendering engines for some time now, in order to accurately capture certain illumination effects. In the same spirit, in this paper, we propose an implementation of progressive photon mapping entirely on the rasterisation pipeline, which is agnostic to the specific GPU architecture, in order to synthesise images at interactive rates. While any GPU ray tracing architecture can be used for photon mapping, performing ray traversal in image space minimises acceleration data structure construction time and supports arbitrarily complex and fully dynamic geometry. Furthermore, this strategy maximises data structure reuse by encompassing rasterisation, ray tracing and photon gathering tasks in a single data structure. Both eye and light paths of arbitrary depth are traced on multi-view deep G-buffers, and photon flux is gathered by a properly adapted multi-view photon splatting. In contrast to previous methods exploiting rasterisation to some extent, due to our novel indirect photon splatting approach, any event combination present in photon mapping is captured. We evaluate our method using typical test scenes and scenarios for photon mapping methods and show how our approach outperforms typical GPU-based progressive photon mapping.

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Acknowledgements

The Bathroom scene was based on a model from https://www.cgtrader.com/, and the Fireplace and Sponza Atrium models were downloaded from McGuire’s Computer Graphics Archive  [15]. The remaining scenes were created by the authors.

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Correspondence to Iordanis Evangelou.

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Evangelou, I., Papaioannou, G., Vardis, K. et al. Rasterisation-based progressive photon mapping. Vis Comput 36, 1993–2004 (2020). https://doi.org/10.1007/s00371-020-01897-3

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