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Compressed bounding volume hierarchies for efficient ray tracing of disperse hair

Published: 10 October 2018 Publication History

Abstract

Ray traced human hair is becoming more and more ubiquitous in photorealistic image synthesis. Despite hierarchical data structures for accelerated ray tracing, performance suffers from the bad separability inherent with ensembles of hair strands. We propose a compressed acceleration data structure that improves separability by adaptively subdividing hair fibers. Compression is achieved by storing quantized as well as oriented bounding boxes and an indexing scheme to specify curve segments instead of storing them.
We trade memory for speed, as our approach may use more memory, however, in cases of highly curved hair we can double the number of traversed rays per second over prior work. With equal memory we still achieve a speed-up of up to 30%, with equal performance we can reduce memory by up to 30%.

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{WBW*14} Woop S., Benthin C., Wald I., Johnson G., Tabellion E.: Exploiting local orientation similarity for efficient ray traversal of hair and fur. In Proceedings of High Performance Graphics (Aire-la-Ville, Switzerland, Switzerland, 2014), HPG '14, Eurographics Association, pp. 41--49. 1, 2, 3, 4
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      cover image Guide Proceedings
      EG VMV '18: Proceedings of the Conference on Vision, Modeling, and Visualization
      October 2018
      169 pages

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      Eurographics Association

      Goslar, Germany

      Publication History

      Published: 10 October 2018

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