PCL and ParaView - Connecting the Dots

Abstract

We introduce a novel open-source framework for analyzing and exploring point cloud datasets and algorithms. This is done by integrating the Point Cloud Library (PCL) within ParaView, a parallel scientific visualization tool. In particular, we demonstrate that by wrapping PCL algorithms as VTK <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> filters, we can leverage PCL's functionality in an interactive, easy-to-use manner within ParaView. The proposed approach enables rapid algorithm development in a coherent framework without the need to write custom visualization code. We illustrate the advantages of the framework with usage examples such as segmentation, data annotation and Python integration. Additionally, we build upon ParaView's inherent parallelization capabilities and present two strong scaling experiments that demonstrate near-linear scaling performance gains in a multi-processor setup.