搜索资源列表
yasuo
- 三维激光点云数据压缩算法,通过先设置压缩率,再随机选点,最后实现数据压缩-Three-dimensional laser point cloud data compression algorithm, by setting the compression rate, and then randomly selected points, and finally to achieve data compression
RGB2lab
- 三维彩色点云RGB颜色转换成LAB颜色空间 ,很好的区分树木-3D Point Cloud rgb to lab
3d-pointcloud-view
- 基于MATLAB的三维彩色点云的显示,真彩色,支持.ply格式,内附.ply格式的点云,-MATLAB 3D Point Cloud Processing
geo_feature_image
- 用于通过三维激光点云数据生成二维的地理参考特征图像,此处以高程作为特征-Used by 3 d laser point cloud data to generate two-dimensional geographical characteristics of reference image, the elevation as features
cloud-point
- 此代码基于c++标准库,opencv和pcl点云库,可实现对摄像头调参,调用摄像头视频并读取画面中点的三维坐标获取点云数据-This code is based on c++ standard library, opencv and pcl point cloud library, can achieve the camera tuning, call the camera video and read the middle of the screen coordinates of the th
pcsc
- 计算机视觉当中,三维重建,点云程序.具体运行为 java PointCloudsShowCenter [-s scale] <point-cloud-files...>-3D construction in CV pointcloud usage:java PointCloudsShowCenter [-s scale] <point-cloud-files...>
Reconstruction_of_tree
- 基于激光点云数据,利用VS2015完成树木模型三维重建(Reconstruction of tree)
三维重建过程中的点云数据处理技术研究_唐靖
- clear all close all clc a=[-16. x=a(:,1);z=a(:,3); scatter(x,z)(Satan made near the Little Buddha pull; bone necrosis planning)
Source code
- 在opencv上实现双目测距主要步骤是: 1.双目校正和标定,获得摄像头的参数矩阵: 进行标定得出俩摄像头的参数矩阵 cvStereoRectify 执行双目校正 initUndistortRectifyMap 分别生成两个图像校正所需的像素映射矩阵 cvremap 分别对两个图像进行校正 2.立体匹配,获得视差图: stereoBM生成视差图 预处理: 图像归一化,减少亮度差别,增强纹理 匹配过程: 滑动sad窗口,沿着水平线进行匹配搜索,由于校正后左右图片平行,左图
Desktop
- 用于四步相移法解相位,运用点云进行三维重建(Four step phase shifting method for phase unwrapping)