Auto Splats: Dynamic Point Cloud Visualization on the GPU

Reinhold Preiner, Stefan Jeschke, Michael Wimmer
Auto Splats: Dynamic Point Cloud Visualization on the GPU
In Proceedings of Eurographics Symposium on Parallel Graphics and Visualization, pages 139-148. May 2012.
[draft]

Information

Abstract

Capturing real-world objects with laser-scanning technology has become an everyday task. Recently, the acquisition of dynamic scenes at interactive frame rates has become feasible. A high-quality visualization of the resulting point cloud stream would require a per-frame reconstruction of object surfaces. Unfortunately, reconstruction computations are still too time-consuming to be applied interactively. In this paper we present a local surface reconstruction and visualization technique that provides interactive feedback for reasonably sized point clouds, while achieving high image quality. Our method is performed entirely on the GPU and in screen pace, exploiting the efficiency of the common rasterization pipeline. The approach is very general, as no assumption is made about point connectivity or sampling density. This naturally allows combining the outputs of multiple scanners in a single visualization, which is useful for many virtual and augmented reality applications.

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BibTeX

@inproceedings{preiner_2012_AS,
  title =      "Auto Splats: Dynamic Point Cloud Visualization on the GPU",
  author =     "Reinhold Preiner and Stefan Jeschke and Michael Wimmer",
  year =       "2012",
  abstract =   "Capturing real-world objects with laser-scanning technology
               has become an everyday task. Recently, the acquisition of
               dynamic scenes at interactive frame rates has become
               feasible. A high-quality visualization of the resulting
               point cloud stream would require a per-frame reconstruction
               of object surfaces. Unfortunately, reconstruction
               computations are still too time-consuming to be applied
               interactively. In this paper we present a local surface
               reconstruction and visualization technique that provides
               interactive feedback for reasonably sized point clouds,
               while achieving high image quality. Our method is performed
               entirely on the GPU and in screen pace, exploiting the
               efficiency of the common rasterization pipeline. The
               approach is very general, as no assumption is made about
               point connectivity or sampling density. This naturally
               allows combining the outputs of multiple scanners in a
               single visualization, which is useful for many virtual and
               augmented reality applications.",
  month =      may,
  booktitle =  "Proceedings of Eurographics Symposium on Parallel Graphics
               and Visualization",
  editor =     "H. Childs and T. Kuhlen",
  isbn =       " 978-3-905674-35-4",
  location =   "Cagliari",
  organization = "Eurographics Association 2012",
  pages =      "139--148",
  keywords =   "point clouds, surface reconstruction, point rendering, Auto
               Splats, KNN search, GPU rendering, point based rendering",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2012/preiner_2012_AS/",
}