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Dieses Dokument ist leider nur in Englisch verfügbar. 
Abstract |
Pictures |
Movies |
Data sets |
Download |
Papers
Point Cloud Visualization
Abstract
Numerical particle simulations and astronomical observations create huge
data sets containing uncorrelated 3D points of varying size. These data
sets cannot be visualized interactively by simply rendering millions of
colored points for each frame. Therefore, in many visualization
applications a scalar density corresponding to the point distribution is
resampled on a regular grid for direct volume rendering. However, many fine
details are usually lost for voxel resolutions which still allow interactive
visualization on standard workstations. Since no surface geometry is
associated with our data sets, the recently introduced point-based rendering
algorithms cannot be applied as well.
We propose to accelerate the visualization of scattered point
data by a hierarchical data structure based on a PCA clustering procedure.
By traversing this structure for each frame we can trade-off rendering speed
vs. image quality. Our scheme also reduces memory consumption by using
quantized relative coordinates and it allows for fast sorting of
semi-transparent clusters. We analyze various software and hardware
implementations of our renderer and demonstrate that we can now visualize
data sets with tens of millions of points interactively with sub-pixel
screenspace error on current PC graphics hardware employing advanced vertex
shader functionality.
Pictures
Important note: The images are highly sensitive to your current
display gamma. We provide images for display gammas of 1.0, 1.5, 1.9, and 2.4.
With the following test images you can determine your current gamma settings.
The left and right parts of the image with the correct gamma setting should
look almost equivalent, when viewed from a greater distance.
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| Gamma 1.0 | |
Gamma 1.5 | |
Gamma 1.9 | |
Gamma 2.4 |
| Figure 1: Display gamma selection |
None of these matches? Please try this in order
to determine your real display gamma.
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1.0
1.5
1.9
2.4 |
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1.0
1.5
1.9
2.4 |
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1.0
1.5
1.9
2.4 |
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SPH simulation (1M pts) | |
Galaxy formation (540K pts, sorted) | |
Reversible apollonian parking (sorted, point sprites) | |
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| Figure 3: Other data sets |
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1.0
1.5
1.9
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| Adaptive vs. full data rendering | |
Software vs. OpenGL rasterization |
Figure 4: Rendering differences - contrast enhanced by 400% |
Movies
High resolution movies are encoded with the DivX 5.02 MPeg4 video codec. Low resolution movies are encoded with an MPeg1 codec. Again, please be sure to select the correct gamma version.
Data Sets
The data sets of the
Virgo Cosortium
that have been used are publically available at
http://www.mpa-garching.mpg.de/Virgo/data_download.html. For more information and sources of other data see the file README.datasets in the source archive.
Download
The source of the program is licensed under the GPL, V2 or later:
pointcloud-2006-03-31.tgz (1.1MB)
One data set of the
Virgo Consortium
is available in already clustered form:
virgo.pcld.gz (280MB)
Attention! This file is large!
pointcould can read GZip-compressed pcld files, but as this can be much slower
than reading the uncompressed file (depending on your disk and CPU speed), you
might want to uncompress virgo.pcld.gz first.
Papers and Technical Reports
- M. Hopf, M. Luttenberger, T. Ertl,
Hierarchical splatting of scattered 4D data (submitted version only),
Computer Graphics and Applications,
24:4, pp. 64-72, IEEE, 2004.
(9 pages)
- M. Hopf, T. Ertl,
Hierarchical Splatting of Scattered Data
(pdf),
Vis '03.
(8 pages, 4.1 MB)
Matthias Hopf
<mat@mshopf.de>
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