点云库 (Point Cloud Library，PCL)
The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing.
点云库 (PCL) 是一个独立的大型开放项目，用于 2D/3D 图像和点云处理。
PCL is released under the terms of the BSD license, and thus free for commercial and research use. We are financially supported by a consortium of commercial companies, with our own non-profit organization, Open Perception. We would also like to thank individual donors and contributors that have been helping the project.
PCL 是根据 BSD 许可条款发行的，因此可免费用于商业和研究用途。由商业公司财团和我们自己的非营利组织 Open Perception 提供财务支持。我们还要感谢一直在帮助该项目的个人捐助者和贡献者。
perception [pəˈsepʃn]：n. 认识能力，知觉，感觉，洞察力，看法，获取
The PCL framework contains numerous state-of-the art algorithms including filtering, feature estimation, surface reconstruction, registration, model fitting and segmentation. These algorithms can be used, for example, to filter outliers from noisy data, stitch 3D point clouds together, segment relevant parts of a scene, extract keypoints and compute descriptors to recognize objects in the world based on their geometric appearance, and create surfaces from point clouds and visualize them – to name a few.
PCL 框架包含许多最新算法，包括滤波、特征估计、曲面重建、配准、模型拟合和分割。这些算法可用于，例如，从嘈杂的数据中过滤出异常值，将 3D 点云缝合在一起，分割场景的相关部分，提取关键点并计算描述符以根据物体的几何外观识别世界上的物体，并从中创建表面点云并将其可视化 - 仅举几例。
PCL is cross-platform, and has been successfully compiled and deployed on Linux, MacOS, Windows, and Android. To simplify development, PCL is split into a series of smaller code libraries, that can be compiled separately. This modularity is important for distributing PCL on platforms with reduced computational or size constraints.
PCL 是跨平台的，并且已成功编译并部署在 Linux、MacOS、Windows 和 Android 上。为了简化开发，将 PCL 分为一系列较小的代码库，可以分别进行编译。这种模块化对于在计算或大小约束减少的平台上部署 PCL 至关重要。
Another way to think about PCL is as a graph of code libraries, similar to the Boost set of C++ libraries.
考虑 PCL 的另一种方法是使用代码库图，类似于 Boost of C++ 库。
modularity [,mɒdjʊ'lærɪtɪ]：n. 模块性
OpenCV 是 2D 信息获取与处理的结晶，PCL 在 3D 信息获取与处理上具有同等地位。
References
http://www.pclcn.org/
http://pointclouds.org/
http://docs.pointclouds.org/trunk/
http://www.pointclouds.org/documentation/
https://github.com/PointCloudLibrary
