StructurePointcloud

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The preprocessing module in IEEE PAMI 2013: A Framework for Automatic Modeling from Point Cloud Data

Structures the unstructured LiDAR data captured using an airborne scanner, into memory-manageable components which can be further processed in parallel.

The size of the "tiles" or "geospatial bounding boxes" can be adjusted by changing the preprocessor flags: RES_x, RES_Y, RES_Z.

The copyright for the included bilateral filtering code belongs to Sylvain Paris and Frédo Durand.

References:

1. IEEE PAMI 2013: A Framework for Automatic Modeling from Point Cloud Data
2. IEEE CVPR 2009: Automatic reconstruction of cities from remote sensor data

More information about this work: www.poullis.org

Technical details:

• The project file is provided for Code::Blocks IDE.
• It requires the libraries Image Magick and fftw3.
• A small sample file is provided in the data folder.

IMPORTANT: To use this software, please consider citing the following in any resulting publication:

@article{poullis2013framework, title={A Framework for Automatic Modeling from Point Cloud Data}, author={Poullis, Charalambos}, journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on}, volume={35}, number={11}, pages={2563--2575}, year={2013}, publisher={IEEE} }

@inproceedings{poullis2009automatic, title={Automatic reconstruction of cities from remote sensor data}, author={Poullis, Charalambos and You, Suya}, booktitle={Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on}, pages={2775--2782}, year={2009}, organization={IEEE} }