试验了好久了，终于成功了！用OpenNI获取彩色和深度数据流，转化成OpenCV的Mat图像格式。
对相机进行标定，获取相机的内部参数：
Calibration results after optimization (with uncertainties): //优化后的参数值Focal Length: fc = [ 510.99171 513.71815 ] ? [ 1.99569 2.13975 ] //焦距Principal point: cc = [ 324.12889 236.29232 ] ? [ 3.66214 3.41361 ] //关键点Skew: alpha_c = [ 0.00000 ] ? [ 0.00000 ] => angle of pixel axes = 90.00000 ? 0.00000 degreesDistortion: kc = [ 0.06196 -0.25035 -0.00173 0.00098 0.00000 ] ? [ 0.02152 0.08623 0.00242 0.00263 0.00000 ]Pixel error: err = [ 0.33426 0.40108 ]
设（u， v）是像素坐标系的坐标，（Xw， Yw，Zw）是世界坐标系的坐标。
则标定后可以通过（u， v）求出（Xw， Yw），公式如下：
Xw = (u – u0) * Zw / fx;
Yw = (v – v0) *Zw / fy;
其中（u0，v0）是光轴与像素平面的交点坐标。
效果图如下：
代码如下：
<span style="font-size:18px;">#include <pcl/visualization/cloud_viewer.h>#include <iostream>#include <pcl/io/io.h>#include <pcl/io/pcd_io.h>#include <opencv2/opencv.hpp>int user_data;const double u0 = 319.52883;const double v0 = 271.61749;const double fx = 528.57523;const double fy = 527.57387;void viewerOneOff (pcl::visualization::PCLVisualizer& viewer){viewer.setBackgroundColor (0.0, 0.0, 0.0);}int main (){pcl::PointCloud<pcl::PointXYZRGB> cloud_a;pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZRGB>);cv::Mat color = cv::imread("Image1.jpg");cv::Mat depth = cv::imread("cc.jpg");int rowNumber = color.rows;int colNumber = color.cols;cloud_a.width = rowNumber;cloud_a.height = colNumber;cloud_a.points.resize(cloud_a.width*cloud_a.height);for (unsigned int u = 0; u < rowNumber; ++u){for (unsigned int v = 0; v < colNumber; ++v){unsigned int num = u*rowNumber + v;double Xw = 0, Yw = 0, Zw = 0;Zw = ((double)depth.at<uchar>(u,v)) / 255.0 * 10001.0;Xw = (u-u0) * Zw / fx;Yw = (v-v0) * Zw / fy;cloud_a.points[num].b = (int)color.at<cv::Vec3b>(u,v)[0];cloud_a.points[num].g = (int)color.at<cv::Vec3b>(u,v)[1];cloud_a.points[num].r = (int)color.at<cv::Vec3b>(u,v)[2];cloud_a.points[num].x = Xw;cloud_a.points[num].y = Yw;cloud_a.points[num].z = Zw;}}*cloud = cloud_a;pcl::visualization::CloudViewer viewer("Cloud Viewer");viewer.showCloud(cloud);viewer.runOnVisualizationThreadOnce (viewerOneOff);while (!viewer.wasStopped ()){user_data = 9;}return 0;}</span>
，而这些目标凝结成希望的萌芽，在汗水与泪水浇灌下，绽放成功之花。
