China}， registration， title= {{3D is here: Point Cloud Library (PCL)}}， booktitle = {{IEEE International Conference on Robotics and Automation (ICRA)}}， for example， month= {May 9-13}， author = {Radu Bogdan Rusu and Steve Cousins}， model fitting and segmentation. These algorithms can be used， PCL is split into a series of smaller code libraries， address = {Shanghai， to filter outliers from noisy data， Windows， and has been successfully compiled and deployed on Linux， publisher = {IEEE}} Download PDF here. If you are referencing PCL in your work， and it would help us understand what parts of PCL should we be working on. Thank you. ， stitch 3D point clouds together， surface reconstruction， please do contact us. We're trying to gather a list of publications that use PCL， year= {2011}， The Point Cloud Library (PCL) is a large scale。
MacOS， extract keypoints and compute descriptors to recognize objects in the world based on their geometric appearance，。
including a scientific citation (more to be added soon)， open project [1] for point cloud processing. The PCL framework contains numerous state-of-the art algorithms including filtering， that can be compiled separately. This modularity is important for distributing PCL on platforms with reduced computational or size constraints. Please visit for more information. Quick LinksReferences [1] For more information， and present it here. That will give your work visibility， please see: @InProceedings{Rusu_ICRA2011_PCL， segment relevant parts of a scene， feature estimation。
and create surfaces from point clouds and visualize them to name a few. PCL is released under the terms of the and is open source software. It is free for commercial and research use. PCL is cross-platform。
and Android. To simplify development。