depth_to_pointcloud.cpp

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#include "image_cb_detector/depth_to_pointcloud.h"
 
 
 
DepthToPointCloud::DepthToPointCloud()
{
  // TODO Auto-generated constructor stub
 
}
 
DepthToPointCloud::~DepthToPointCloud()
{
  // TODO Auto-generated destructor stub
}
 
void DepthToPointCloud::initialize(sensor_msgs::ImageConstPtr depth_msg,
                                   sensor_msgs::CameraInfoConstPtr camera_info_msg)
{
  if (!depth_msg || !camera_info_msg)
  {
    return;
  }
 
  std::size_t width = depth_msg->width;
  std::size_t height = depth_msg->height;
 
  if (width != projection_map_x_.size() || height !=projection_map_y_.size())
  {
    // Procompute 3D projection matrix
    //
    // The following computation of center_x,y and fx,fy duplicates
    // code in the image_geometry package, but this avoids dependency
    // on OpenCV, which simplifies releasing rviz.
 
    // Use correct principal point from calibration
    float center_x = camera_info_msg->P[2] - camera_info_msg->roi.x_offset;
    float center_y = camera_info_msg->P[6] - camera_info_msg->roi.y_offset;
 
    // Combine unit conversion (if necessary) with scaling by focal length for computing (X,Y)
    double scale_x = camera_info_msg->binning_x > 1 ? (1.0 / camera_info_msg->binning_x) : 1.0;
    double scale_y = camera_info_msg->binning_y > 1 ? (1.0 / camera_info_msg->binning_y) : 1.0;
 
    double fx = camera_info_msg->P[0] * scale_x;
    double fy = camera_info_msg->P[5] * scale_y;
 
    float constant_x = 1.0f / fx;
    float constant_y = 1.0f / fy;
 
    projection_map_x_.resize(width);
    projection_map_y_.resize(height);
    std::vector<float>::iterator projX = projection_map_x_.begin();
    std::vector<float>::iterator projY = projection_map_y_.begin();
 
    // precompute 3D projection matrix
    for (int v = 0; v < height; ++v, ++projY)
      *projY = (v - center_y) * constant_y;
 
    for (int u = 0; u < width; ++u, ++projX)
      *projX = (u - center_x) * constant_x;
  }
}