https://github.com/huangcongqing/pcl-learning

🔥PCL（Point Cloud Library）点云库学习记录
https://github.com/huangcongqing/pcl-learning

3d-detection 3d-reconstruction 3d-representation 3d-segmentation pcl pcl-library pcl-viewer ros self-driving-car

Last synced: 3 days ago
JSON representation

🔥PCL（Point Cloud Library）点云库学习记录

Host: GitHub
URL: https://github.com/huangcongqing/pcl-learning
Owner: HuangCongQing
License: mit
Created: 2019-04-16T13:20:08.000Z (over 6 years ago)
Default Branch: master
Last Pushed: 2025-04-21T16:55:48.000Z (6 months ago)
Last Synced: 2025-04-21T17:44:40.817Z (6 months ago)
Topics: 3d-detection, 3d-reconstruction, 3d-representation, 3d-segmentation, pcl, pcl-library, pcl-viewer, ros, self-driving-car
Language: C++
Homepage: https://www.bilibili.com/video/BV1HS4y1y7AB
Size: 34.3 MB
Stars: 1,738
Watchers: 26
Forks: 419
Open Issues: 4
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

          
# pcl

![](https://img.shields.io/badge/pcl-learning-v0.1-brightgreen)

![](https://img.shields.io/badge/pcl->=v1.9-red)

[![GitHub stars](https://img.shields.io/github/stars/HuangCongQing/pcl-learning.svg?style=social&label=Stars)](https://github.com/murufeng/awesome_lightweight_networks)

[![GitHub forks](https://img.shields.io/github/forks/HuangCongQing/pcl-learning.svg?style=social&label=Forks)](https://github.com/murufeng/awesome_lightweight_networks)

![visitors](https://visitor-badge.glitch.me/badge?page_id=HuangCongQing/pcl-learning) 

PCL（Point Cloud Library）点云库  **个人开发环境：Ubuntu18.04**

* 如有疑问，微信：shuangyu_ai 

  * **Plus: _可承接点云处理相关项目，欢迎私聊_**

  * **PCL微信交流群二维码每周都更新一次，请关注公众号【双愚】后台回复PCL加群**

  * 更多自动驾驶相关交流群，欢迎扫码加入：[自动驾驶感知(PCL/ROS+DL)：技术交流群汇总(新版)](https://mp.weixin.qq.com/s?__biz=MzI4OTY1MjA3Mg==&mid=2247486575&idx=1&sn=3145b7a5e9dda45595e1b51aa7e45171&chksm=ec2aa068db5d297efec6ba982d6a73d2170ef09a01130b7f44819b01de46b30f13644347dbf2#rd) 

* [**【本仓库测试pcd数据】**](./data)

**墙裂建议先看下：[PCL(Point Cloud Library)学习指南&资料推荐](https://zhuanlan.zhihu.com/p/268524083)**

**PCL学习入门指南&代码实践(最新版)入门视频：  https://www.bilibili.com/video/BV1HS4y1y7AB**

**代码对应系列笔记：[PCL(Point Cloud Library)学习记录（最新）](https://www.yuque.com/huangzhongqing/pcl)**



**相关项目实战:**

* 3D-MOT(多目标检测和追踪):

  [https://github.com/HuangCongQing/3D-LIDAR-Multi-Object-Tracking/tree/kitti](https://github.com/HuangCongQing/3D-LIDAR-Multi-Object-Tracking/tree/kitti)

    * 需要学习ROS：https://github.com/HuangCongQing/ROS

@[双愚](https://github.com/HuangCongQing/pcl-learning) , 若fork或star请注明来源

> * 点云数据的处理可以采用获得广泛应用的Point Cloud Library (点云库，PCL库)。

> * PCL库是一个最初发布于2013年的开源C++库。它实现了大量点云相关的通用算法和高效的数据管理。

> * 支持多种操作系统平台，可在Windows、Linux、Android、Mac OS X、部分嵌入式实时系统上运行。如果说OpenCV是2D信息获取与处理的技术结晶，那么PCL在3D信息获取与处理上，就与OpenCV具有同等地位

> * PCL是BSD授权方式，可以免费进行商业和学术应用。

* 英文官网：https://pcl.readthedocs.io/projects/tutorials/en/latest/#

  * https://pointclouds.org/

* GitHub：https://github.com/PointCloudLibrary/pcl

  * 学习基于pcl1.9.1：https://github.com/PointCloudLibrary/pcl/tree/pcl-1.9.1

**Tips:**

* ubuntu下使用PCL，需要写**CMakeLists.txt**文件，然后编译才可以生成可执行文件.

* 可执行文件在build文件夹下，所以运行可执行文件时，后面添加参数的pcd文件，应放在build文件夹下才能获取到。**（注意文件路径）**

* `make -j `   (-j 自动多线程， -j4 四线程)

## 目录contents

> ***建议必学**

* [**【本仓库测试pcd数据】**](./data)

* [00base](00base)

##### step1（must）

* [* 08 io 输入输出](08IO输入输出)  [[doc](https://www.yuque.com/huangzhongqing/pcl/mt2yo5)]

* [* 09 filters 滤波](09filters滤波)  [[doc](https://www.yuque.com/huangzhongqing/pcl/ai96k5)]

* [* 10 features 特征](10features特征)  [[doc](https://www.yuque.com/huangzhongqing/pcl/kf9kmf)]

##### step2

* [* 02kdtree k维tree](02kdtree)  [[doc](https://www.yuque.com/huangzhongqing/pcl/uffamg#w9i1y)]

* [* 03octree 八叉树](03octree)  [[doc](https://www.yuque.com/huangzhongqing/pcl/habl9h)]

* [* 04search](04search):  [[doc](https://www.yuque.com/huangzhongqing/pcl/qs4wx2)]

* [05sample consensus  抽样一致性模块](05sampleconsensus抽样一致性模块)  [[doc](https://www.yuque.com/huangzhongqing/pcl/ivtxgx)]

* [06range-images深度图像](06range-images深度图像)  [[doc](https://www.yuque.com/huangzhongqing/pcl/hxeyrz)]

##### step3（根据个人需要）

* [11 surface表面 ](11surface表面)  [[doc](https://www.yuque.com/huangzhongqing/pcl/yfrd0w)]

* [12 segmentation分割](12segmentation分割)  [[doc](https://www.yuque.com/huangzhongqing/pcl/kg7wvi)]

* [13 recognition识别](13recognition识别)  [[doc](https://www.yuque.com/huangzhongqing/pcl/hpgc39)]

* [14 registration配准](14registration配准)  [[doc](https://www.yuque.com/huangzhongqing/pcl/zg7alz)]  

* [* 15 visualization可视化](15visualization可视化)   [[doc](https://www.yuque.com/huangzhongqing/pcl/rmexll)]

* [16 keypoints关键点](16keypoints关键点)   [[doc](https://www.yuque.com/huangzhongqing/pcl/twi0mt)]

* [07tracking跟踪](07tracking跟踪/tracking.md)   [[doc](https://www.yuque.com/huangzhongqing/pcl/em72xa)]

## 编译过程

```shell

mkdir build

cd build

cmake .. // 对上一级进行编译

make  // 生成可执行文件

./executedemo  // 运行可执行文件

```

## 实战项目

不理解的地方,欢迎提issue: https://github.com/HuangCongQing/pcl-learning/issues

* 3D-MOT(多目标检测和追踪)

  * https://github.com/HuangCongQing/3D-LIDAR-Multi-Object-Tracking/tree/kitti

* 3D点云目标检测&语义分割-SOTA方法,代码,论文,数据集等

  * https://github.com/HuangCongQing/3D-Point-Clouds

## 相关链接

* 公众号：点云PCL

* https://github.com/Yochengliu/awesome-point-cloud-analysis

* https://github.com/QingyongHu/SoTA-Point-Cloud

* https://github.com/PointCloudLibrary/pcl

* 参考书籍：点云库PCL学习教程，朱德海，北京航空航天大学出版社

* Plus：ROS学习-https://github.com/HuangCongQing/ROS

**入门资料：**

- **PCL学习入门指南&代码实践(最新版)入门视频：  https://www.bilibili.com/video/BV1HS4y1y7AB**

- **视频**：[bilibili-PCL点云库官网教程](https://space.bilibili.com/504859351/channel/detail?cid=130387)

- **点云库PCL学习教程书籍每章总结：**[https://github.com/MNewBie/PCL-Notes](https://github.com/MNewBie/PCL-Notes)

- 百度网盘资料：

链接：[https://pan.baidu.com/s/1ziq8s_kj5QpM8eXO_d6RJg](https://pan.baidu.com/s/1ziq8s_kj5QpM8eXO_d6RJg)
提取码：g6ny


**代码实践资料：**

- 官方各模块示例(和对应的对象函数对照着看)【英文】：[https://pcl.readthedocs.io/projects/tutorials/en/latest/#](https://pcl.readthedocs.io/projects/tutorials/en/latest/#)

- 官方各模块对应的对象和函数【英文】：

  - [https://pointclouds.org/documentation/modules.html](https://pointclouds.org/documentation/modules.html)

  - [https://pointclouds.org/](https://pointclouds.org/) 点击网站中的12宫图，没一格对应一个模块的对象函数详解

- [黑马机器人系列文档：PCL-3D点云](http://robot.czxy.com/docs/pcl/)：[http://robot.czxy.com/docs/pcl/](http://robot.czxy.com/docs/pcl/)

- [CSDN博主系列文章PCL学习(64篇)](https://www.cnblogs.com/li-yao7758258/category/954066.html)：[https://www.cnblogs.com/li-yao7758258/category/954066.html](https://www.cnblogs.com/li-yao7758258/category/954066.html)

## Citation 

If you find this project useful in your research, please consider cite:

```

@misc{pcl-learning2020,

    title={A Complete Study Guide on How to Learn PCL (Point Cloud Library).},

    author={Chongqing, Huang},

    howpublished = {\url{https://github.com/HuangCongQing/pcl-learning}},

    year={2020}

}

```

### 欢迎交流

后续会根据逐步完善，欢迎大家提出宝贵意见，也欢迎大家提issue pr，还有star⭐️。

可以领取优惠加入星球使劲向我提问哈~





> PLus: 创建了一个知识星球 **【自动驾驶感知(PCL/ROS+DL)】** 专注于自动驾驶感知领域，包括传统方法(PCL点云库,ROS)和深度学习（目标检测+语义分割）方法。同时涉及Apollo，Autoware(基于ros2)，BEV感知，三维重建，SLAM(视觉+激光雷达) ，模型压缩（蒸馏+剪枝+量化等），自动驾驶模拟仿真，自动驾驶数据集标注&数据闭环等自动驾驶全栈技术，欢迎扫码二维码加入，一起登顶自动驾驶的高峰！

微信公众号：**【双愚】**（huang_chongqing） 聊科研技术,谈人生思考,欢迎关注~



**往期推荐：**

1. [本文不提供职业建议，却能助你一生](https://mp.weixin.qq.com/s/rBR62qoAEeT56gGYTA0law)

2. [聊聊我们大学生面试](https://mp.weixin.qq.com/s?__biz=MzI4OTY1MjA3Mg==&mid=2247484016&idx=1&sn=08bc46266e00572e46f3e5d9ffb7c612&chksm=ec2aae77db5d276150cde1cb1dc6a53e03eba024adfbd1b22a048a7320c2b6872fb9dfef32aa&scene=178&cur_album_id=2253272068899471368#rd)

3. [清华大学刘知远：好的研究方法从哪来](https://mp.weixin.qq.com/s?__biz=MzI4OTY1MjA3Mg==&mid=2247486340&idx=1&sn=6c5f69bb37d91a343b1a1e7f6929ddae&chksm=ec2aa783db5d2e95ba4c472471267721cafafbe10c298a6d5fae9fed295f455a72f783872249&scene=178&cur_album_id=1855544495514140673#rd)

**最后，如果您想要支持我的工作，请扫描下面的二维码**



### License

Copyright (c) [双愚](https://github.com/HuangCongQing/pcl-learning). All rights reserved.

Licensed under the [MIT](./LICENSE) License.

ecosyste.ms

Data

Tools

Indexes

Applications

Experiments

Awesome

https://github.com/huangcongqing/pcl-learning

Awesome Lists containing this project

README