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3D-reconstruction-master
- 3d 重建 包括特征点的提取，匹配，以及三维点云的建立(3d reconstruction ,including feature detection and 3 D points cloud ,the change from 2D to 3D)
tricurv
- 根据点云数据计算各个顶点的主曲率，主方向，高斯曲率和平均曲率(Calculated according to each vertex main curvature of point cloud data, the main direction, gaussian curvature and mean curvature)
LoadPointCloud
- 直接动态加载点云模型 由.xyz的点云数据 转化为 .osgb格式 然后可以直接用这个软件加载(Point cloud model of direct dynamic loading)
我的
- 可以提取txt格式点云边界，包括内边界(The TXT format can be extracted from the point cloud boundary, including the inner boundary)
point cloud
- 本文件主要针对具体的项目，对点云数据进行处理(This document deals with point cloud data primarily for specific projects)
icpCpp
- ICP算法是实现多幅点云配准，配准效果好，精度高。(ICP algorithm is to achieve a number of point cloud registration, registration effect is good, high precision.)
icp
- 3维点云的配准基本算法，基于pcl库的icp算法程序(pointcloud registration)
kincet+pcl获取点云
- 利用kinect和PCL点云库，将深度图像转换生成三维点云(Kinect and PCL point cloud libraries are used to convert depth images to generate 3D point clouds)
Txt2Las
- 用于转换点云数据格式，txt格式转换为常见的las格式，方便处理(Used to convert point cloud data format, TXT format into a common Las format, easy to handle)
find_feature_contour
- 输入3D点云，并进行傅里叶变换以及获取其轮廓特征。
ICP
- 点云配准过程，就是求一个两个点云之间的旋转平移矩阵（rigid transform or euclidean transform 刚性变换或欧式变换），将源点云(source cloud)变换到目标点云(target cloud)相同的坐标系下。(Matching of two sets oPoint cloud registration process, is to get a two point cloud between the translation and rotation matri
基于VTk的点云显示
- 基于VTk的点云显示，构网（Delaunay Tin，包含二维，三维，及TEN）。附有详细的代码注释，也有实例数据。-(VTk based point cloud display (Delaunay, Tin, including 2D, 3D, and TEN). With detailed code notes, there are examples of data. -)
moveXYZ
- 能够实现点云的平移，旋转缩放，基于PCL点云库，内有说明文档，实现快速点云操作(To achieve the translation of point cloud, rotate, zoom)
激光雷达
- 在Linux平台下，使用QT5.7.0.实现八线激光雷达点云数据的聚类。数据采集于真实的场景。采用蒙特卡洛和ABD聚类算法实现聚类。(In Linux platform, we use QT5.7.0. to realize the clustering of point cloud data of eight line lidar. Data is collected in real scenes. Monte Carlo and ABD clustering algorithms are u
point_cloud_reduction
- 自己开发的一种点云降噪方法，可以去除物体主体之外的部分的点云数据（物体点云数据为三维扫描仪获得）(A point cloud noise reduction method developed by ourselves can remove part of the cloud data outside the main body of the object (object cloud data is obtained for a three-dimensional scanner))
point_cloud_compression.tar
- 通过ros话题传输point cloud点云数据，然后在解析出来。(Transmitting point cloud data through ROS topic)
C++ 三维点云的圆柱面拟合
- 通过已有的点云数据或者三角网格数据最小二乘拟合圆柱面(Least square fitting cylinder by point cloud or tri-mesh)
20171017084327
- 一份带反射强度的会议室点云文件，可以用来初学者使用。(A conference room cloud file with reflection intensity, which can be used for beginners.)
NurbsProj
- 开发的可将扫描获得点云数据 生成nurbs曲面的小程序(Development can be scanned point cloud data generated nurbs surfaces of the small programs)
point3d
- 直接运行TestMyCrust.m, 读取点云txt,或者直接加载mat文件 运行需要几分钟，耐心等待 完成后运行trianglenormal.m, 生成三角面片的法向量 运行完成得到tri.txt（组成三角面片的点的编号信息）,trinormal.txt(每个三角面片法向量数值)，diandian.txt(每个点云信息) 然后将三个数据当做stl_gen.exe的输入文件，得到trisuface.stl文件(run TestMyCrust.m, read point cloud fil