ParaView/PCL Plugin: Difference between revisions

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=== What is the PCL Plugin ? ===
=== What is the PCL Plugin ? ===
The PCL plugin for ParaView allows users to access filters from the [http://pointclouds.org/ Point Cloud Processing Library (PCL)] within ParaView. The plugin wraps PCL algorithms as VTK filters.  The plugin also provides Python bindings for the filters using VTK's python wrapping, thus enabling fast prototyping and integration with NumPy and SciPy. With point cloud data loaded in ParaView, users can interactively apply PCL algorithms, color the point clouds by different attributes, and quickly compose complex processing pipelines to explore the point cloud data.
The PCL plugin for ParaView allows users to access filters from the [http://pointclouds.org/ Point Cloud Processing Library (PCL)] within ParaView. The plugin wraps PCL algorithms as VTK filters.  The plugin also provides Python bindings for the filters using VTK's python wrapping, thus enabling fast prototyping and integration with NumPy and SciPy. With point cloud data loaded in ParaView, users can interactively apply PCL algorithms, color the point clouds by different attributes, and quickly compose complex processing pipelines to explore the point cloud data.
[[Image:PCL_Plugin_Video_Screenshot.png|link=http://vimeo.com/43975225|center|border]]


=== Currently supported PCL algorithms ===
=== Currently supported PCL algorithms ===
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=== News ===
=== News ===


* We will present the PCL plugin and give a demo at this year's CVPR in Providence, RI (Sunday, June 16, 4.55pm - 6.30pm).  Browse the [http://www-sop.inria.fr/manifestations/pcp2012/|PCP workshop website] for more information.
* We will present the PCL plugin and give a demo at this year's CVPR in Providence, RI (Sunday, June 16, 4.55pm - 6.30pm).  Browse the [http://www-sop.inria.fr/manifestations/pcp2012/ PCP workshop website] for more information.


=== References ===
=== References ===
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* '''[[ParaView/PCL_Plugin/Download_And_Build_Instructions|Download & Build Instructions]]'''
* '''[[ParaView/PCL_Plugin/Download_And_Build_Instructions|Download & Build Instructions]]'''
* '''Developer Guide'''
* '''[[Media:DevGuidev1.0a.pdf|Developer Guide]]'''
* '''[[ParaView/PCL_Plugin/Tutorials|Tutorials]]'''
* '''[[ParaView/PCL_Plugin/Tutorials|Tutorials]]'''
|}<br />
|}<br />

Latest revision as of 15:55, 16 June 2012

Pclpluginlogo.png

What is the PCL Plugin ?

The PCL plugin for ParaView allows users to access filters from the Point Cloud Processing Library (PCL) within ParaView. The plugin wraps PCL algorithms as VTK filters. The plugin also provides Python bindings for the filters using VTK's python wrapping, thus enabling fast prototyping and integration with NumPy and SciPy. With point cloud data loaded in ParaView, users can interactively apply PCL algorithms, color the point clouds by different attributes, and quickly compose complex processing pipelines to explore the point cloud data.

PCL Plugin Video Screenshot.png

Currently supported PCL algorithms

At the current stage of development, the plugin provides several of PCL's core algorithms for point cloud processing, including:

  • Euclidean cluster extraction
  • Robust plane/cylinder fitting (using RANSAC)
  • Surface normal estimation
  • VoxelGrid filter for downsampling
  • Radius-based outlier removal

News

  • We will present the PCL plugin and give a demo at this year's CVPR in Providence, RI (Sunday, June 16, 4.55pm - 6.30pm). Browse the PCP workshop website for more information.

References

If you are using the plugin for your project, please cite the following paper:

  • P. Marion, R. Kwitt, B. Davis and M. Gschwandtner, PCL and ParaView - Connecting the Dots, Proceedings of the IEEE International Workshop on Point Cloud Processing (PCP '12), 2012 (held in conjunction with CVPR '12)

Here's the corresponding Bibtex entry:

@inproceedings{Marion12a,
  author    = {P.~Marion and R.~Kwitt, B.~Davis and M. Gschwandtner},
  title     = {PCL and ParaView - Connecting the Dots},
  booktitle = {CVPR Workshop on Point Cloud Processing (PCP)},
  year      = 2012}
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