コード例 #1
0
void D3DCloudProjector::projectCloud(int id, const sensor_msgs::PointCloud& data, const std::vector<int>& interest_region_indices) {
  MatrixXf& oriented = orienter_->oriented_clouds_[id];

  // -- Get a copy of the projected points.
  MatrixXf projected(oriented.rows(), 2);
  int c=0;
  for(int i=0; i<3; ++i) {
    if(i == axis_of_projection_)
      continue;
    projected.col(c) = oriented.col(i);
    ++c;
  }

  // -- Transform into pixel units.  projected is currently in meters, centered at 0.
  //projected *= pixels_per_meter_;
  for(int i=0; i<projected.rows(); ++i) {
    projected(i, 0) *= pixels_per_meter_;
    projected(i, 1) *= pixels_per_meter_;
  }
  
  
  // -- Find min and max of u and v.  TODO: noise sensitivity?
  // u is the col number in the image plane, v is the row number.
  float min_v = FLT_MAX;
  float min_u = FLT_MAX;
  float max_v = -FLT_MAX;
  float max_u = -FLT_MAX;
  for(int i=0; i<projected.rows(); ++i) {
    float u = projected(i, 0);
    float v = projected(i, 1);
    if(u < min_u)
      min_u = u;
    if(u > max_u)
      max_u = u;
    if(v < min_v)
      min_v = v;
    if(v > max_v)
      max_v = v;
  }

  // -- Translate to coordinate system where (0,0) is the upper right of the image.
  for(int i=0; i<projected.rows(); ++i) {
    projected(i, 0) -= min_u;
    projected(i, 1) = max_v - projected(i, 1);
  }
  
  // -- Get the max depth.
  float max_depth = -FLT_MAX;
  float min_depth = FLT_MAX;
  for(int i=0; i<oriented.rows(); ++i) {
    if(oriented(i, axis_of_projection_) > max_depth)
      max_depth = oriented(i, axis_of_projection_);
    if(oriented(i, axis_of_projection_) < min_depth)
      min_depth = oriented(i, axis_of_projection_);
  }

  // -- Compute the normalized depths.  Depths are between 0 and 1, with 1 meaning closest and 0 meaning furthest.
  VectorXf depths = oriented.col(axis_of_projection_);
  if(axis_of_projection_ == 1)
    depths = -depths;
  depths = depths.cwise() - depths.minCoeff();
  depths = depths / depths.maxCoeff();
  
      
  
  // -- Fill the IplImages.
  assert(sizeof(float) == 4);
  CvSize size = cvSize(ceil(max_u - min_u), ceil(max_v - min_v));
  IplImage* acc = cvCreateImage(size, IPL_DEPTH_32F, 1);
  IplImage* intensity = cvCreateImage(size, IPL_DEPTH_32F, 1);
  IplImage* depth = cvCreateImage(size, IPL_DEPTH_32F, 1);
  cvSetZero(acc);
  cvSetZero(depth);
  cvSetZero(intensity);
  assert(projected.rows() == (int)interest_region_indices.size());
  for(int i=0; i<projected.rows(); ++i) {
    int row = floor(projected(i, 1));
    int col = floor(projected(i, 0));

    // Update accumulator.
    assert(interest_region_indices[i] < (int)data.channels[0].values.size() && (int)interest_region_indices[i] >= 0);
    ((float*)(acc->imageData + row * acc->widthStep))[col]++;

    // Add to intensity values.
    float val = (float)data.channels[0].values[interest_region_indices[i]] / 255.0 * (3.0 / 4.0) + 0.25;
    assert(val <= 1.0 && val >= 0.0);
    ((float*)(intensity->imageData + row * intensity->widthStep))[col] += val;

    // Add to depth values.
    ((float*)(depth->imageData + row * depth->widthStep))[col] += depths(i); //
  }
  
  // -- Normalize by the number of points falling in each pixel.
  for(int v=0; v<acc->height; ++v) {
    float* intensity_ptr = (float*)(intensity->imageData + v * intensity->widthStep);
    float* depth_ptr = (float*)(depth->imageData + v * depth->widthStep);
    float* acc_ptr = (float*)(acc->imageData + v * acc->widthStep);
    for(int u=0; u<acc->width; ++u) {
      if(*acc_ptr == 0) {
	*intensity_ptr = 0;
	*depth_ptr = 0;
      }
      else {
	*intensity_ptr = *intensity_ptr / *acc_ptr;
	*depth_ptr = *depth_ptr / *acc_ptr;
      }

      intensity_ptr++;
      depth_ptr++;
      acc_ptr++;
    }
  }

  // -- Store images.
  depth_projections_.push_back(depth);
  intensity_projections_.push_back(intensity);

  // -- Debugging.
  if(debug_) {
    float scale = 10;
    IplImage* intensity_big = cvCreateImage(cvSize(((float)intensity->width)*scale, ((float)intensity->height)*scale), intensity->depth, intensity->nChannels);
    cvResize(intensity, intensity_big, CV_INTER_AREA);

    IplImage* depth_big = cvCreateImage(cvSize(((float)depth->width)*scale, ((float)depth->height)*scale), depth->depth, depth->nChannels);
    cvResize(depth, depth_big, CV_INTER_AREA);

    CVSHOW("Intensity Image", intensity_big);
    CVSHOW("Depth Image", depth_big);
    cvWaitKey(0);
    cvDestroyWindow("Intensity Image");
    cvDestroyWindow("Depth Image");
  }
  
  // -- Clean up.
  cvReleaseImage(&acc);
}