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Preprocessing module in IEEE PAMI 2013: A Framework for Automatic Modeling from Point Cloud Data
This project forked from charalambos/structurepointcloud
Preprocessing module in IEEE PAMI 2013: A Framework for Automatic Modeling from Point Cloud Data
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, YOU MUST CITE 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} }
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