ACM SIGGRAPH 2007 Papers 2007
DOI: 10.1145/1275808.1276490
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A hardware architecture for surface splatting

Abstract: We present a novel architecture for hardware-accelerated rendering of point primitives. Our pipeline implements a refined version of EWA splatting, a high quality method for antialiased rendering of point sampled representations. A central feature of our design is the seamless integration of the architecture into conventional, OpenGL-like graphics pipelines so as to complement triangle-based rendering. The specific properties of the EWA algorithm required a variety of novel design concepts including a ternary … Show more

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Cited by 11 publications
(7 citation statements)
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References 34 publications
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“…One of the possibilities to address this issue would be an implementation which exploits the GPU for general purpose programming. Another approach could compute the visibility function much more accurately by using specialized hardware extensions to current GPUs which support a reduced A‐Buffer or by employing an extended dedicated hardware architecture such as [WHA*07]. As our current implementation uses a constant number of samples per frame, the sampling could be varied adaptively for each point based on its motion and shading changes over time in a future work.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…One of the possibilities to address this issue would be an implementation which exploits the GPU for general purpose programming. Another approach could compute the visibility function much more accurately by using specialized hardware extensions to current GPUs which support a reduced A‐Buffer or by employing an extended dedicated hardware architecture such as [WHA*07]. As our current implementation uses a constant number of samples per frame, the sampling could be varied adaptively for each point based on its motion and shading changes over time in a future work.…”
Section: Discussionmentioning
confidence: 99%
“…EWA splatting has been implemented on conventional GPUs either by employing textured quads to approximate the points [RPZ02] or by making use of advanced features of GPUs [ZRB*04, BHZK05, ZP06, GBP06]. Recently, a dedicated hardware architecture for EWA surface splatting has been presented [WHA*07, HSA*08]. Reconstruction methods for rendering point sets [ABCO*01, GG07] have been investigated as well, either through raytracing [AKP*05] or a dynamic upsampling approach which directly splats the generated samples [GGG08].…”
Section: Related Workmentioning
confidence: 99%
“…Finally, the splats in the rendering queue are used as input for the traditional two-pass EWA filter described in [38]. Several methods for computing the sizes of the projected splats were tested [38,39,40,41]. The splat bounding box computation algorithm described in [41] resulted in the best performance-quality relationship and all results reported in this paper applied it.…”
Section: 2mentioning
confidence: 99%
“…Apart from these multipass splatting methods, several alternative point-rendering techniques have been presented; in particular, a ''single-pass'' splatting technique [36,37], dedicated splatting hardware [38], and ray tracing of points [39][40][41]. The ''single-pass'' splatting technique proposed by Zhang and Pajarola [36,37] has to compute groups of non-overlapping splats (in object space) and is therefore less suitable for large, dynamic point sets.…”
Section: Related Workmentioning
confidence: 99%
“…The ''single-pass'' splatting technique proposed by Zhang and Pajarola [36,37] has to compute groups of non-overlapping splats (in object space) and is therefore less suitable for large, dynamic point sets. While the dedicated hardware published by Weyrich et al [38] achieves promising performance results, the prototypical hardware cannot provide the rendering performance of splatting techniques implemented on today's GPUs. Ray tracing of points was first published by Schaufler and Jensen [39] and led to work by Adamson and Alexa [40], and Wald and Seidel [41].…”
Section: Related Workmentioning
confidence: 99%