3D is here: Point Cloud Library (PCL)

TLDR

Low‑cost 3D sensors such as Kinect and advances in point‑cloud processing have made 3D perception increasingly vital in robotics and other domains, and PCL provides an advanced, community‑supported framework for these tasks. This paper introduces PCL, a recent initiative aimed at delivering a comprehensive point‑cloud perception library. PCL offers state‑of‑the‑art algorithms for filtering, feature estimation, surface reconstruction, registration, model fitting, and segmentation, and the paper outlines its implementation strategies.

Abstract

With the advent of new, low-cost 3D sensing hardware such as the Kinect, and continued efforts in advanced point cloud processing, 3D perception gains more and more importance in robotics, as well as other fields. In this paper we present one of our most recent initiatives in the areas of point cloud perception: PCL (Point Cloud Library - http://pointclouds.org). PCL presents an advanced and extensive approach to the subject of 3D perception, and it's meant to provide support for all the common 3D building blocks that applications need. The library contains state-of-the art algorithms for: filtering, feature estimation, surface reconstruction, registration, model fitting and segmentation. PCL is supported by an international community of robotics and perception researchers. We provide a brief walkthrough of PCL including its algorithmic capabilities and implementation strategies.