range_image.hpp

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#include "pcl/win32_macros.h"

namespace pcl
{

template <typename PointCloudType> void 
RangeImage::createFromPointCloud(const PointCloudType& point_cloud, float angular_resolution, float max_angle_width, float max_angle_height,
                                 const Eigen::Affine3f& sensor_pose, RangeImage::CoordinateFrame coordinate_frame,
                                 float noise_level, float min_range, int border_size)
{
  //MEASURE_FUNCTION_TIME;
  
  
  //std::cout << "Starting to create range image from "<<point_cloud.points.size()<<" points.\n";
  
  angular_resolution_ = angular_resolution;
  angular_resolution_reciprocal_ = 1.0f / angular_resolution_;
  
  width = lrint(floor(max_angle_width*angular_resolution_reciprocal_));
  height = lrint(floor(max_angle_height*angular_resolution_reciprocal_));
  image_offset_x_ = image_offset_y_ = 0;  // TODO: FIX THIS
  is_dense = false;
  
  getCoordinateFrameTransformation(coordinate_frame, to_world_system_);
  to_world_system_ = sensor_pose * to_world_system_;
  
  getInverse(to_world_system_, to_range_image_system_);
  //std::cout << "to_world_system_ is\n"<<to_world_system_<<"\nand to_range_image_system_ is\n"<<to_range_image_system_<<"\n\n";
  
  unsigned int size = width*height;
  points.clear();
  points.resize(size, unobserved_point);
  
  int top=height, right=-1, bottom=-1, left=width;
  doZBuffer(point_cloud, noise_level, min_range, top, right, bottom, left);
  
  cropImage(border_size, top, right, bottom, left);
  
  recalculate3DPointPositions();
}

template <typename PointCloudTypeWithViewpoints> void 
RangeImage::createFromPointCloudWithViewpoints(const PointCloudTypeWithViewpoints& point_cloud, float angular_resolution,
                                               float max_angle_width, float max_angle_height, RangeImage::CoordinateFrame coordinate_frame,
                                               float noise_level, float min_range, int border_size)
{
  Eigen::Vector3f average_viewpoint = getAverageViewPoint(point_cloud);
  
  Eigen::Affine3f sensor_pose = (Eigen::Affine3f)Eigen::Translation3f(average_viewpoint);

  createFromPointCloud(point_cloud, angular_resolution, max_angle_width, max_angle_height, sensor_pose, coordinate_frame, noise_level, min_range, border_size);
  
  //change3dPointsToLocalCoordinateFrame();
}

template <typename PointCloudType> void
RangeImage::createFromPointCloudWithKnownSize(const PointCloudType& point_cloud, float angular_resolution,
                                              const Eigen::Vector3f& point_cloud_center, float point_cloud_radius,
                                              const Eigen::Affine3f& sensor_pose, RangeImage::CoordinateFrame coordinate_frame,
                                              float noise_level, float min_range, int border_size)
{
  //MEASURE_FUNCTION_TIME;
  
  //std::cout << "Starting to create range image from "<<point_cloud.points.size()<<" points.\n";
  
  angular_resolution_ = angular_resolution;
  angular_resolution_reciprocal_ = 1.0f / angular_resolution_;
  
  getCoordinateFrameTransformation(coordinate_frame, to_world_system_);
  to_world_system_ = sensor_pose * to_world_system_;
  getInverse(to_world_system_, to_range_image_system_);
  
  float max_angle_size = getMaxAngleSize(sensor_pose, point_cloud_center, point_cloud_radius);
  int pixel_radius = lrint(ceil(0.5f*max_angle_size*angular_resolution_reciprocal_));
  width = height = 2*pixel_radius;
  is_dense = false;
  
  image_offset_x_ = image_offset_y_ = 0;
  int center_pixel_x, center_pixel_y;
  getImagePoint(point_cloud_center, center_pixel_x, center_pixel_y);
  image_offset_x_ = (std::max)(0, center_pixel_x-pixel_radius);
  image_offset_y_ = (std::max)(0, center_pixel_y-pixel_radius);
  //std::cout << PVARC(image_offset_x_)<<PVARN(image_offset_y_);
  //std::cout << PVARC(width)<<PVARN(height);
  //std::cout << PVARAN(angular_resolution_);

  points.clear();
  points.resize(width*height, unobserved_point);
  
  int top=height, right=-1, bottom=-1, left=width;
  doZBuffer(point_cloud, noise_level, min_range, top, right, bottom, left);
  
  cropImage(border_size, top, right, bottom, left);
  
  recalculate3DPointPositions();
}

template <typename PointCloudType> void 
RangeImage::doZBuffer(const PointCloudType& point_cloud, float noise_level, float min_range, int& top, int& right, int& bottom, int& left)
{
  typedef typename PointCloudType::PointType PointType2;
  const std::vector<PointType2, Eigen::aligned_allocator<PointType2> >& points2 = point_cloud.points;
  
  unsigned int size = width*height;
  int* counters = new int[size];
  ERASE_ARRAY(counters, size);
  
  top=height; right=-1; bottom=-1; left=width;
  
  float x_real, y_real, range_of_current_point;
  int x, y;
  for (typename std::vector<PointType2, Eigen::aligned_allocator<PointType2> >::const_iterator it=points2.begin(); it!=points2.end(); ++it)
  {
    if (!hasValidXYZ(*it))  // Check for NAN etc
      continue;
    Vector3fMapConst current_point = it->getVector3fMap();
    
    this->getImagePoint(current_point, x_real, y_real, range_of_current_point);
    this->real2DToInt2D(x_real, y_real, x, y);
    
    if (range_of_current_point < min_range|| !isInImage(x, y))
      continue;
    //std::cout << "("<<current_point[0]<<", "<<current_point[1]<<", "<<current_point[2]<<") falls into pixel "<<x<<","<<y<<".\n";
    
    // Do some minor interpolation by checking the three closest neighbors to the point, that are not filled yet.
    int floor_x = lrint (floor (x_real)), floor_y = lrint (floor (y_real)),
        ceil_x  = lrint (ceil (x_real)),  ceil_y  = lrint (ceil (y_real));
    
    int neighbor_x[4], neighbor_y[4];
    neighbor_x[0]=floor_x; neighbor_y[0]=floor_y;
    neighbor_x[1]=floor_x; neighbor_y[1]=ceil_y;
    neighbor_x[2]=ceil_x;  neighbor_y[2]=floor_y;
    neighbor_x[3]=ceil_x;  neighbor_y[3]=ceil_y;
    //std::cout << x_real<<","<<y_real<<": ";
    
    for (int i=0; i<4; ++i)
    {
      int n_x=neighbor_x[i], n_y=neighbor_y[i];
      //std::cout << n_x<<","<<n_y<<" ";
      if (n_x==x && n_y==y)
        continue;
      if (isInImage(n_x, n_y))
      {
        int neighbor_array_pos = n_y*width + n_x;
        if (counters[neighbor_array_pos]==0)
        {
          float& neighbor_range = points[neighbor_array_pos].range;
          neighbor_range = (pcl_isinf(neighbor_range) ? range_of_current_point : (std::min)(neighbor_range, range_of_current_point));
          top=(std::min)(top, n_y); right=(std::max)(right, n_x); bottom=(std::max)(bottom, n_y); left=(std::min)(left, n_x);
        }
      }
    }
    //std::cout <<std::endl;
    
    // The point itself
    int arrayPos = y*width + x;
    float& range_at_image_point = points[arrayPos].range;
    int& counter = counters[arrayPos];
    bool addCurrentPoint=false, replace_with_current_point=false;
    
    if (counter==0)
    {
      replace_with_current_point = true;
    }
    else
    {
      if (range_of_current_point < range_at_image_point-noise_level)
      {
        replace_with_current_point = true;
      }
      else if (fabs(range_of_current_point-range_at_image_point)<=noise_level)
      {
        addCurrentPoint = true;
      }
    }
    
    if (replace_with_current_point)
    {
      counter = 1;
      range_at_image_point = range_of_current_point;
      top=(std::min)(top, y); right=(std::max)(right, x); bottom=(std::max)(bottom, y); left=(std::min)(left, x);
      //std::cout << "Adding point "<<x<<","<<y<<"\n";
    }
    else if (addCurrentPoint)
    {
      ++counter;
      range_at_image_point += (range_of_current_point-range_at_image_point)/counter;
    }
  }
  
  delete[] counters;
}

void 
RangeImage::getImagePoint(float x, float y, float z, float& image_x, float& image_y, float& range) const 
{
  Eigen::Vector3f point(x, y, z);
  getImagePoint(point, image_x, image_y, range);
}

void 
RangeImage::getImagePoint(float x, float y, float z, float& image_x, float& image_y) const 
{
  float range;
  getImagePoint(x, y, z, image_x, image_y, range);
}

void 
RangeImage::getImagePoint(float x, float y, float z, int& image_x, int& image_y) const 
{
  float image_x_float, image_y_float;
  getImagePoint(x, y, z, image_x_float, image_y_float);
  real2DToInt2D(image_x_float, image_y_float, image_x, image_y);
}

void 
RangeImage::getImagePoint(const Eigen::Vector3f& point, float& image_x, float& image_y, float& range) const 
{
  Eigen::Vector3f transformedPoint = to_range_image_system_ * point;
  range = transformedPoint.norm();
  float angle_x = atan2f(transformedPoint[0], transformedPoint[2]),
        angle_y = asinf(transformedPoint[1]/range);
  getImagePointFromAngles(angle_x, angle_y, image_x, image_y);
  //std::cout << "("<<point[0]<<","<<point[1]<<","<<point[2]<<")"
            //<< " => ("<<transformedPoint[0]<<","<<transformedPoint[1]<<","<<transformedPoint[2]<<")"
            //<< " => "<<angle_x<<","<<angle_y<<" => "<<image_x<<","<<image_y<<"\n";
}

void 
RangeImage::getImagePoint(const Eigen::Vector3f& point, int& image_x, int& image_y, float& range) const {
  float image_x_float, image_y_float;
  getImagePoint(point, image_x_float, image_y_float, range);
  real2DToInt2D(image_x_float, image_y_float, image_x, image_y);
}

void 
RangeImage::getImagePoint(const Eigen::Vector3f& point, float& image_x, float& image_y) const
{
  float range;
  getImagePoint(point, image_x, image_y, range);
}

void 
RangeImage::getImagePoint(const Eigen::Vector3f& point, int& image_x, int& image_y) const
{
  float image_x_float, image_y_float;
  getImagePoint(point, image_x_float, image_y_float);
  real2DToInt2D(image_x_float, image_y_float, image_x, image_y);
}

float 
RangeImage::checkPoint(const Eigen::Vector3f& point, PointWithRange& point_in_image) const
{
  int image_x, image_y;
  float range;
  getImagePoint(point, image_x, image_y, range);
  if (!isInImage(image_x, image_y))
    point_in_image = unobserved_point;
  else
    point_in_image = getPoint(image_x, image_y);
  return range;
}

float 
RangeImage::getRangeDifference(const Eigen::Vector3f& point) const
{
  int image_x, image_y;
  float range;
  getImagePoint(point, image_x, image_y, range);
  if (!isInImage(image_x, image_y))
    return -std::numeric_limits<float>::infinity ();
  float image_point_range = getPoint(image_x, image_y).range;
  if (pcl_isinf(image_point_range))
  {
    if (image_point_range > 0.0f)
      return std::numeric_limits<float>::infinity ();
    else
      return -std::numeric_limits<float>::infinity ();
  }
  return image_point_range - range;
}

void 
RangeImage::getImagePointFromAngles(float angle_x, float angle_y, float& image_x, float& image_y) const
{
  image_x = (angle_x*cosf(angle_y) + float(M_PI))*angular_resolution_reciprocal_ - image_offset_x_;
  image_y = (angle_y + 0.5f*float(M_PI))*angular_resolution_reciprocal_ - image_offset_y_;
}

void 
RangeImage::real2DToInt2D(float x, float y, int& xInt, int& yInt) const
{
  xInt = lrint(x); yInt = lrint(y);
}

bool 
RangeImage::isInImage(int x, int y) const
{
  return x>=0 && x<(int)width && y>=0 && y<(int)height;
}

bool 
RangeImage::isValid(int x, int y) const
{
  return isInImage(x,y) && pcl_isfinite(getPoint(x,y).range);
}

bool 
RangeImage::isValid(int index) const
{
  return pcl_isfinite(getPoint(index).range);
}

bool 
RangeImage::isObserved(int x, int y) const
{
  if (!isInImage(x,y) || (pcl_isinf(getPoint(x,y).range)&&getPoint(x,y).range<0.0f))
    return false;
  return true;
}

bool 
RangeImage::isMaxRange(int x, int y) const
{
  float range = getPoint(x,y).range;
  return pcl_isinf(range) && range>0.0f;
}

const PointWithRange& 
RangeImage::getPointConsideringWrapAround(int image_x, int image_y) const
{
  if (!isObserved(image_x, image_y))
  {
    float angle_x, angle_y, image_x_f, image_y_f;
    getAnglesFromImagePoint(image_x, image_y, angle_x, angle_y);
    angle_x = normAngle(angle_x);  angle_y = normAngle(angle_y);
    getImagePointFromAngles(angle_x, angle_y, image_x_f, image_y_f);
    int new_image_x, new_image_y;
    real2DToInt2D(image_x_f, image_y_f, new_image_x, new_image_y);
    if (image_x!=new_image_x || image_y!=new_image_y)
      std::cout << image_x<<","<<image_y << " was change to "<<new_image_x<<","<<new_image_y<<"\n";
    if (!isInImage(new_image_x, new_image_y))
      return unobserved_point;
    image_x=new_image_x; image_y=new_image_y;
  }
  return points[image_y*width + image_x];
}

const PointWithRange& 
RangeImage::getPoint(int image_x, int image_y) const
{
  if (!isInImage(image_x, image_y))
    return unobserved_point;
  return points[image_y*width + image_x];
}

const PointWithRange& 
RangeImage::getPointNoCheck(int image_x, int image_y) const
{
  return points[image_y*width + image_x];
}

PointWithRange& 
RangeImage::getPointNoCheck(int image_x, int image_y)
{
  return points[image_y*width + image_x];
}

PointWithRange& 
RangeImage::getPoint(int image_x, int image_y)
{
  return points[image_y*width + image_x];
}


const PointWithRange& 
RangeImage::getPoint(int index) const
{
  return points[index];
}

const PointWithRange&
RangeImage::getPoint(float image_x, float image_y) const
{
  int x, y;
  real2DToInt2D(image_x, image_y, x, y);
  return getPoint(x, y);
}

PointWithRange& 
RangeImage::getPoint(float image_x, float image_y)
{
  return getPoint(image_x, image_y);
}

void 
RangeImage::getPoint(int image_x, int image_y, Eigen::Vector3f& point) const
{
  //std::cout << getPoint(image_x, image_y)<< " - " << getPoint(image_x, image_y).getVector3fMap()<<"\n";
  point = getPoint(image_x, image_y).getVector3fMap();
}

void 
RangeImage::getPoint(int index, Eigen::Vector3f& point) const
{
  point = getPoint(index).getVector3fMap();
}

const Eigen::Map<const Eigen::Vector3f> 
RangeImage::getEigenVector3f(int x, int y) const
{
  return getPoint(x, y).getVector3fMap();
}

const Eigen::Map<const Eigen::Vector3f> 
RangeImage::getEigenVector3f(int index) const
{
  return getPoint(index).getVector3fMap();
}

void 
RangeImage::calculate3DPoint(float image_x, float image_y, float range, Eigen::Vector3f& point) const 
{
  float angle_x, angle_y;
  //std::cout << image_x<<","<<image_y<<","<<range;
  getAnglesFromImagePoint(image_x, image_y, angle_x, angle_y);
  
  float cosY = cosf(angle_y);
  point = Eigen::Vector3f(range * sinf(angle_x) * cosY, range * sinf(angle_y), range * cosf(angle_x)*cosY);
  point = to_world_system_ * point;
}

void 
RangeImage::calculate3DPoint(float image_x, float image_y, Eigen::Vector3f& point) const
{
  const PointWithRange& point_in_image = getPoint(image_x, image_y);
  calculate3DPoint(image_x, image_y, point_in_image.range, point);
}

void 
RangeImage::calculate3DPoint(float image_x, float image_y, float range, PointWithRange& point) const {
  point.range = range;
  Eigen::Vector3f tmp_point;
  calculate3DPoint(image_x, image_y, range, tmp_point);
  point.x=tmp_point[0];  point.y=tmp_point[1];  point.z=tmp_point[2];
}

void 
RangeImage::calculate3DPoint(float image_x, float image_y, PointWithRange& point) const
{
  const PointWithRange& point_in_image = getPoint(image_x, image_y);
  calculate3DPoint(image_x, image_y, point_in_image.range, point);
}

void 
RangeImage::getAnglesFromImagePoint(float image_x, float image_y, float& angle_x, float& angle_y) const 
{
  angle_y = (image_y+image_offset_y_)*angular_resolution_ - 0.5f*float(M_PI);
  float cos_angle_y = cosf(angle_y);
  angle_x = (cos_angle_y==0.0f ? 0.0f : ((image_x+image_offset_x_)*angular_resolution_ - float(M_PI))/cos_angle_y);
}

float 
RangeImage::getImpactAngle(int x1, int y1, int x2, int y2) const
{
  if (!isInImage(x1, y1) || !isInImage(x2,y2))
    return -std::numeric_limits<float>::infinity ();
  return getImpactAngle(getPoint(x1,y1),getPoint(x2,y2));
}

float 
RangeImage::getImpactAngle(const PointWithRange& point1, const PointWithRange& point2) const {
  if ((pcl_isinf(point1.range)&&point1.range<0) || (pcl_isinf(point2.range)&&point2.range<0))
    return -std::numeric_limits<float>::infinity ();
  
  float r1 = (std::min)(point1.range, point2.range),
        r2 = (std::max)(point1.range, point2.range);
  float impact_angle = 0.5f*M_PI;
  
  if (pcl_isinf(r2)) {
    if (r2 > 0.0f && !pcl_isinf(r1))
      impact_angle = 0.0f;
  }
  else if (!pcl_isinf(r1)) {
    float r1Sqr = r1*r1,
          r2Sqr = r2*r2,
          dSqr  = squaredEuclideanDistance(point1, point2),
          d     = sqrtf(dSqr);
    float cos_impact_angle = (r2Sqr + dSqr - r1Sqr)/(2.0f*r2*d);
    cos_impact_angle = (std::max)(0.0f, (std::min)(1.0f, cos_impact_angle));
    impact_angle = acosf(cos_impact_angle);  // Using the cosine rule
  }
  
  if (point1.range > point2.range)
    impact_angle = -impact_angle;
  
  return impact_angle;
}

float 
RangeImage::getAcutenessValue(const PointWithRange& point1, const PointWithRange& point2) const
{
  float impact_angle = getImpactAngle(point1, point2);
  if (pcl_isinf(impact_angle))
    return -std::numeric_limits<float>::infinity ();
  float ret = 1.0f - fabs(impact_angle)/(0.5f*M_PI);
  if (impact_angle < 0.0f)
    ret = -ret;
  //if (fabs(ret)>1)
    //std::cout << PVARAC(impact_angle)<<PVARN(ret);
  return ret;
}

float 
RangeImage::getAcutenessValue(int x1, int y1, int x2, int y2) const
{
  if (!isInImage(x1, y1) || !isInImage(x2,y2))
    return -std::numeric_limits<float>::infinity ();
  return getAcutenessValue(getPoint(x1,y1), getPoint(x2,y2));
}

const Eigen::Vector3f 
RangeImage::getSensorPos() const
{
  return Eigen::Vector3f(to_world_system_(0,3), to_world_system_(1,3), to_world_system_(2,3));
}

void 
RangeImage::getSurfaceAngleChange(int x, int y, int radius, float& angle_change_x, float& angle_change_y) const
{
  angle_change_x = angle_change_y = -std::numeric_limits<float>::infinity ();
  if (!isValid(x,y))
    return;
  Eigen::Vector3f point;
  getPoint(x, y, point);
  Eigen::Affine3f transformation = getTransformationToViewerCoordinateFrame(point);
  
  if (isObserved(x-radius, y) && isObserved(x+radius, y))
  {
    Eigen::Vector3f transformed_left;
    if (isMaxRange(x-radius, y))
      transformed_left = Eigen::Vector3f(0.0f, 0.0f, -1.0f);
    else
    {
      Eigen::Vector3f left;
      getPoint(x-radius, y, left);
      transformed_left = -(transformation * left);
      //std::cout << PVARN(transformed_left[1]);
      transformed_left[1] = 0.0f;
      transformed_left.normalize();
    }
    
    Eigen::Vector3f transformed_right;
    if (isMaxRange(x+radius, y))
      transformed_right = Eigen::Vector3f(0.0f, 0.0f, 1.0f);
    else
    {
      Eigen::Vector3f right;
      getPoint(x+radius, y, right);
      transformed_right = transformation * right;
      //std::cout << PVARN(transformed_right[1]);
      transformed_right[1] = 0.0f;
      transformed_right.normalize();
    }
    angle_change_x = transformed_left.dot(transformed_right);
    angle_change_x = (std::max)(0.0f, (std::min)(1.0f, angle_change_x));
    angle_change_x = acosf(angle_change_x);
  }
  
  if (isObserved(x, y-radius) && isObserved(x, y+radius))
  {
    Eigen::Vector3f transformed_top;
    if (isMaxRange(x, y-radius))
      transformed_top = Eigen::Vector3f(0.0f, 0.0f, -1.0f);
    else
    {
      Eigen::Vector3f top;
      getPoint(x, y-radius, top);
      transformed_top = -(transformation * top);
      //std::cout << PVARN(transformed_top[0]);
      transformed_top[0] = 0.0f;
      transformed_top.normalize();
    }
    
    Eigen::Vector3f transformed_bottom;
    if (isMaxRange(x, y+radius))
      transformed_bottom = Eigen::Vector3f(0.0f, 0.0f, 1.0f);
    else
    {
      Eigen::Vector3f bottom;
      getPoint(x, y+radius, bottom);
      transformed_bottom = transformation * bottom;
      //std::cout << PVARN(transformed_bottom[0]);
      transformed_bottom[0] = 0.0f;
      transformed_bottom.normalize();
    }
    angle_change_y = transformed_top.dot(transformed_bottom);
    angle_change_y = (std::max)(0.0f, (std::min)(1.0f, angle_change_y));
    angle_change_y = acosf(angle_change_y);
  }
}


//inline float RangeImage::getSurfaceChange(const PointWithRange& point, const PointWithRange& neighbor1, const PointWithRange& neighbor2) const
//{
  //if (!pcl_isfinite(point.range) || (!pcl_isfinite(neighbor1.range)&&neighbor1.range<0) || (!pcl_isfinite(neighbor2.range)&&neighbor2.range<0))
    //return -std::numeric_limits<float>::infinity ();
  //if (pcl_isinf(neighbor1.range))
  //{
    //if (pcl_isinf(neighbor2.range))
      //return 0.0f;
    //else
      //return acosf((Eigen::Vector3f(point.x, point.y, point.z)-getSensorPos()).normalized().dot((Eigen::Vector3f(neighbor2.x, neighbor2.y, neighbor2.z)-Eigen::Vector3f(point.x, point.y, point.z)).normalized()));
  //}
  //if (pcl_isinf(neighbor2.range))
    //return acosf((Eigen::Vector3f(point.x, point.y, point.z)-getSensorPos()).normalized().dot((Eigen::Vector3f(neighbor1.x, neighbor1.y, neighbor1.z)-Eigen::Vector3f(point.x, point.y, point.z)).normalized()));
  
  //float d1_squared = squaredEuclideanDistance(point, neighbor1),
        //d1 = sqrtf(d1_squared),
        //d2_squared = squaredEuclideanDistance(point, neighbor2),
        //d2 = sqrtf(d2_squared),
        //d3_squared = squaredEuclideanDistance(neighbor1, neighbor2);
  //float cos_surface_change = (d1_squared + d2_squared - d3_squared)/(2.0f*d1*d2),
        //surface_change = acosf(cos_surface_change);
  //if (pcl_isnan(surface_change))
    //surface_change = float(M_PI);

  //return surface_change;
//}

float 
RangeImage::getMaxAngleSize(const Eigen::Affine3f& viewer_pose, const Eigen::Vector3f& center, float radius)
{
  return 2.0f * asinf(radius/(getTranslation(viewer_pose)-center).norm());
}

Eigen::Vector3f 
RangeImage::getEigenVector3f(const PointWithRange& point)
{
  return Eigen::Vector3f(point.x, point.y, point.z);
}

void 
RangeImage::get1dPointAverage(int x, int y, int delta_x, int delta_y, int no_of_points, PointWithRange& average_point) const
{
  //std::cout << __PRETTY_FUNCTION__<<" called.\n";
  //MEASURE_FUNCTION_TIME;
  float weight_sum = 1.0f;
  average_point = getPoint(x,y);
  if (pcl_isinf(average_point.range))
  {
    if (average_point.range>0.0f)  // The first point is max range -> return a max range point
      return;
    weight_sum = 0.0f;
    average_point.x = average_point.y = average_point.z = average_point.range = 0.0f;
  }
  
  int x2=x, y2=y;
  Vector4fMap average_point_eigen = average_point.getVector4fMap();
  //std::cout << PVARN(no_of_points);
  for (int step=1; step<no_of_points; ++step)
  {
    //std::cout << PVARC(step);
    x2+=delta_x;  y2+=delta_y;
    if (!isValid(x2, y2))
      continue;
    const PointWithRange& p = getPointNoCheck(x2, y2);
    average_point_eigen+=p.getVector4fMap(); average_point.range+=p.range;
    weight_sum += 1.0f;
  }
  if (weight_sum<= 0.0f)
  {
    average_point = unobserved_point;
    return;
  }
  float normalization_factor = 1.0f/weight_sum;
  average_point_eigen *= normalization_factor;
  average_point.range *= normalization_factor;
  //std::cout << PVARN(average_point);
}

float 
RangeImage::getEuclideanDistanceSquared(int x1, int y1, int x2, int y2) const
{
  if (!isObserved(x1,y1)||!isObserved(x2,y2))
    return -std::numeric_limits<float>::infinity ();
  const PointWithRange& point1 = getPoint(x1,y1),
                      & point2 = getPoint(x2,y2);
  if (pcl_isinf(point1.range) && pcl_isinf(point2.range))
    return 0.0f;
  if (pcl_isinf(point1.range) || pcl_isinf(point2.range))
    return std::numeric_limits<float>::infinity ();
  return squaredEuclideanDistance(point1, point2);
}

float 
RangeImage::getAverageEuclideanDistance(int x, int y, int offset_x, int offset_y, int max_steps) const
{
  float average_pixel_distance = 0.0f;
  float weight=0.0f;
  for (int i=0; i<max_steps; ++i)
  {
    int x1=x+i*offset_x,     y1=y+i*offset_y;
    int x2=x+(i+1)*offset_x, y2=y+(i+1)*offset_y;
    float pixel_distance = getEuclideanDistanceSquared(x1,y1,x2,y2);
    if (!pcl_isfinite(pixel_distance))
    {
      //std::cout << x<<","<<y<<"->"<<x2<<","<<y2<<": "<<pixel_distance<<"\n";
      if (i==0)
        return pixel_distance;
      else
        break;
    }
    //std::cout << x<<","<<y<<"->"<<x2<<","<<y2<<": "<<sqrtf(pixel_distance)<<"m\n";
    weight += 1.0f;
    average_pixel_distance += sqrtf(pixel_distance);
  }
  average_pixel_distance /= weight;
  //std::cout << x<<","<<y<<","<<offset_x<<","<<offset_y<<" => "<<average_pixel_distance<<"\n";
  return average_pixel_distance;
}

float 
RangeImage::getImpactAngleBasedOnLocalNormal(int x, int y, int radius) const
{
  if (!isValid(x,y))
    return -std::numeric_limits<float>::infinity ();
  const PointWithRange& point = getPoint(x, y);
  int no_of_nearest_neighbors = pow((double)(radius+1), 2.0);
  Eigen::Vector3f normal;
  if (!getNormalForClosestNeighbors(x, y, radius, point, no_of_nearest_neighbors, normal, 1))
    return -std::numeric_limits<float>::infinity ();
  return deg2rad(90.0f) - acosf(normal.dot((getSensorPos()-getEigenVector3f(point)).normalized()));
}


bool 
RangeImage::getNormal(int x, int y, int radius, Eigen::Vector3f& normal, int step_size) const
{
  VectorAverage3f vector_average;
  for (int y2=y-radius; y2<=y+radius; y2+=step_size)
  {
    for (int x2=x-radius; x2<=x+radius; x2+=step_size)
    {
      if (!isInImage(x2, y2))
        continue;
      const PointWithRange& point = getPoint(x2, y2);
      if (!pcl_isfinite(point.range))
        continue;
      vector_average.add(Eigen::Vector3f(point.x, point.y, point.z));
    }
  }
  if (vector_average.getNoOfSamples() < 3)
    return false;
  Eigen::Vector3f eigen_values, eigen_vector2, eigen_vector3;
  vector_average.doPCA(eigen_values, normal, eigen_vector2, eigen_vector3);
  if (normal.dot((getSensorPos()-vector_average.getMean()).normalized()) < 0.0f)
    normal *= -1.0f;
  return true;
}

float 
RangeImage::getNormalBasedAcutenessValue(int x, int y, int radius) const
{
  float impact_angle = getImpactAngleBasedOnLocalNormal(x, y, radius);
  if (pcl_isinf(impact_angle))
    return -std::numeric_limits<float>::infinity ();
  float ret = 1.0f - impact_angle/(0.5f*M_PI);
  //std::cout << PVARAC(impact_angle)<<PVARN(ret);
  return ret;
}

bool 
RangeImage::getNormalForClosestNeighbors(int x, int y, int radius, const PointWithRange& point,
                                              int no_of_nearest_neighbors, Eigen::Vector3f& normal, int step_size) const
{
  return getNormalForClosestNeighbors(x, y, radius, Eigen::Vector3f(point.x, point.y, point.z), no_of_nearest_neighbors, normal, NULL, step_size);
}

bool 
RangeImage::getNormalForClosestNeighbors(int x, int y, Eigen::Vector3f& normal, int radius) const
{
  if (!isValid(x,y))
    return false;
  int no_of_nearest_neighbors = pow ((double)(radius+1), 2.0);
  return getNormalForClosestNeighbors(x, y, radius, getPoint(x,y).getVector3fMap(), no_of_nearest_neighbors, normal);
}

namespace 
{  // Anonymous namespace, so that this is only accessible in this file
  struct NeighborWithDistance 
  {  // local struct to help us with sorting
    float distance;
    const PointWithRange* neighbor;
    bool operator <(const NeighborWithDistance& other) const { return distance<other.distance;}
  };
}

bool 
RangeImage::getSurfaceInformation (int x, int y, int radius, const Eigen::Vector3f& point, int no_of_closest_neighbors, int step_size,
                                   float& max_closest_neighbor_distance_squared,
                                   Eigen::Vector3f& normal, Eigen::Vector3f& mean, Eigen::Vector3f& eigen_values,
                                   Eigen::Vector3f* normal_all_neighbors, Eigen::Vector3f* mean_all_neighbors,
                                   Eigen::Vector3f* eigen_values_all_neighbors) const
{
  max_closest_neighbor_distance_squared=0.0f;
  normal.setZero(); mean.setZero(); eigen_values.setZero();
  if (normal_all_neighbors!=NULL)
    normal_all_neighbors->setZero();
  if (mean_all_neighbors!=NULL)
    mean_all_neighbors->setZero();
  if (eigen_values_all_neighbors!=NULL)
    eigen_values_all_neighbors->setZero();
  
  int blocksize = pow ((double)(2*radius+1), 2.0);
  
  PointWithRange given_point;
  given_point.x=point[0];  given_point.y=point[1];  given_point.z=point[2];
  
  std::vector<NeighborWithDistance> ordered_neighbors (blocksize);
  int neighbor_counter = 0;
  for (int y2=y-radius; y2<=y+radius; y2+=step_size)
  {
    for (int x2=x-radius; x2<=x+radius; x2+=step_size)
    {
      if (!isValid(x2, y2))
        continue;
      NeighborWithDistance& neighbor_with_distance = ordered_neighbors[neighbor_counter];
      neighbor_with_distance.neighbor = &getPoint(x2, y2);
      neighbor_with_distance.distance = squaredEuclideanDistance(given_point, *neighbor_with_distance.neighbor);
      ++neighbor_counter;
    }
  }
  no_of_closest_neighbors = (std::min)(neighbor_counter, no_of_closest_neighbors);

  std::sort (ordered_neighbors.begin (), ordered_neighbors.begin () + neighbor_counter);  // Normal sort seems to be the fastest method (faster than partial_sort)
  //std::stable_sort(ordered_neighbors, ordered_neighbors+neighbor_counter);
  //std::partial_sort(ordered_neighbors, ordered_neighbors+no_of_closest_neighbors, ordered_neighbors+neighbor_counter);
  
  max_closest_neighbor_distance_squared = ordered_neighbors[no_of_closest_neighbors-1].distance;
  //float max_distance_squared = max_closest_neighbor_distance_squared;
  float max_distance_squared = max_closest_neighbor_distance_squared*4.0f;  // Double the allowed distance value
  //max_closest_neighbor_distance_squared = max_distance_squared;
  
  VectorAverage3f vector_average;
  //for (int neighbor_idx=0; neighbor_idx<no_of_closest_neighbors; ++neighbor_idx)
  int neighbor_idx;
  for (neighbor_idx=0; neighbor_idx<neighbor_counter; ++neighbor_idx)
  {
    if (ordered_neighbors[neighbor_idx].distance > max_distance_squared)
      break;
    //std::cout << ordered_neighbors[neighbor_idx].distance<<"\n";
    vector_average.add(ordered_neighbors[neighbor_idx].neighbor->getVector3fMap());
  }
  
  if (vector_average.getNoOfSamples() < 3)
    return false;
  //std::cout << PVARN(vector_average.getNoOfSamples());
  Eigen::Vector3f eigen_vector2, eigen_vector3;
  vector_average.doPCA(eigen_values, normal, eigen_vector2, eigen_vector3);
  Eigen::Vector3f viewing_direction = (getSensorPos()-point).normalized();
  if (normal.dot(viewing_direction) < 0.0f)
    normal *= -1.0f;
  mean = vector_average.getMean();
  
  if (normal_all_neighbors==NULL)
    return true;
  
  // Add remaining neighbors
  for (int neighbor_idx2=neighbor_idx; neighbor_idx2<neighbor_counter; ++neighbor_idx2)
    vector_average.add(ordered_neighbors[neighbor_idx2].neighbor->getVector3fMap());
  
  vector_average.doPCA(*eigen_values_all_neighbors, *normal_all_neighbors, eigen_vector2, eigen_vector3);
  //std::cout << PVARN(vector_average.getNoOfSamples())<<".\n";
  if (normal_all_neighbors->dot(viewing_direction) < 0.0f)
    *normal_all_neighbors *= -1.0f;
  *mean_all_neighbors = vector_average.getMean();
  
  //std::cout << viewing_direction[0]<<","<<viewing_direction[1]<<","<<viewing_direction[2]<<"\n";
  
  return true;
}

float 
RangeImage::getSquaredDistanceOfNthNeighbor(int x, int y, int radius, int n, int step_size) const
{
  const PointWithRange& point = getPoint(x, y);
  if (!pcl_isfinite(point.range))
    return -std::numeric_limits<float>::infinity ();
  
  int blocksize = pow ((double)(2*radius+1), 2.0);
  std::vector<float> neighbor_distances (blocksize);
  int neighbor_counter = 0;
  for (int y2=y-radius; y2<=y+radius; y2+=step_size)
  {
    for (int x2=x-radius; x2<=x+radius; x2+=step_size)
    {
      if (!isValid(x2, y2) || (x2==x&&y2==y))
        continue;
      const PointWithRange& neighbor = getPointNoCheck(x2,y2);
      float& neighbor_distance = neighbor_distances[neighbor_counter++];
      neighbor_distance = squaredEuclideanDistance(point, neighbor);
    }
  }
  std::sort (neighbor_distances.begin (), neighbor_distances.begin () + neighbor_counter);  // Normal sort seems to be
                                                                      // the fastest method (faster than partial_sort)
  n = (std::min)(neighbor_counter, n);
  return neighbor_distances[n-1];
}


bool 
RangeImage::getNormalForClosestNeighbors(int x, int y, int radius, const Eigen::Vector3f& point, int no_of_nearest_neighbors,
                                                     Eigen::Vector3f& normal, Eigen::Vector3f* point_on_plane, int step_size) const
{
  Eigen::Vector3f mean, eigen_values;
  float used_squared_max_distance;
  bool ret = getSurfaceInformation(x, y, radius, point, no_of_nearest_neighbors, step_size, used_squared_max_distance,
                                   normal, mean, eigen_values);
  
  if (ret)
  {
    if (point_on_plane != NULL)
      *point_on_plane = (normal.dot(mean) - normal.dot(point))*normal + point;
  }
  return ret;
}


float 
RangeImage::getCurvature(int x, int y, int radius, int step_size) const
{
  VectorAverage3f vector_average;
  for (int y2=y-radius; y2<=y+radius; y2+=step_size)
  {
    for (int x2=x-radius; x2<=x+radius; x2+=step_size)
    {
      if (!isInImage(x2, y2))
        continue;
      const PointWithRange& point = getPoint(x2, y2);
      if (!pcl_isfinite(point.range))
        continue;
      vector_average.add(Eigen::Vector3f(point.x, point.y, point.z));
    }
  }
  if (vector_average.getNoOfSamples() < 3)
    return false;
  Eigen::Vector3f eigen_values;
  vector_average.doPCA(eigen_values);
  return eigen_values[0]/eigen_values.sum();
}


template <typename PointCloudTypeWithViewpoints> Eigen::Vector3f 
RangeImage::getAverageViewPoint(const PointCloudTypeWithViewpoints& point_cloud)
{
  Eigen::Vector3f average_viewpoint(0,0,0);
  int point_counter = 0;
  for (unsigned int point_idx=0; point_idx<point_cloud.points.size(); ++point_idx)
  {
    const typename PointCloudTypeWithViewpoints::PointType& point = point_cloud.points[point_idx];
    if (!pcl_isfinite(point.vp_x) || !pcl_isfinite(point.vp_y) || !pcl_isfinite(point.vp_z))
      continue;
    average_viewpoint[0] += point.vp_x;
    average_viewpoint[1] += point.vp_y;
    average_viewpoint[2] += point.vp_z;
    ++point_counter;
  }
  average_viewpoint /= point_counter;
  
  return average_viewpoint;
}

bool 
RangeImage::getViewingDirection(int x, int y, Eigen::Vector3f& viewing_direction) const
{
  if (!isValid(x, y))
    return false;
  viewing_direction = (getPoint(x,y).getVector3fMap()-getSensorPos()).normalized();
  return true;
}

void 
RangeImage::getViewingDirection(const Eigen::Vector3f& point, Eigen::Vector3f& viewing_direction) const
{
  viewing_direction = (point-getSensorPos()).normalized();
}

Eigen::Affine3f 
RangeImage::getTransformationToViewerCoordinateFrame(const Eigen::Vector3f& point) const
{
  Eigen::Affine3f transformation;
  getTransformationToViewerCoordinateFrame(point, transformation);
  return transformation;
}

void 
RangeImage::getTransformationToViewerCoordinateFrame(const Eigen::Vector3f& point, Eigen::Affine3f& transformation) const
{
  Eigen::Vector3f viewing_direction = (point-getSensorPos()).normalized();
  getTransformationFromTwoUnitVectorsAndOrigin(Eigen::Vector3f(0.0f, -1.0f, 0.0f), viewing_direction, point, transformation);
}

void 
RangeImage::getRotationToViewerCoordinateFrame(const Eigen::Vector3f& point, Eigen::Affine3f& transformation) const
{
  Eigen::Vector3f viewing_direction = (point-getSensorPos()).normalized();
  getTransformationFromTwoUnitVectors(Eigen::Vector3f(0.0f, -1.0f, 0.0f), viewing_direction, transformation);
}

inline void
RangeImage::setAngularResolution (float angular_resolution)
{
  angular_resolution_ = angular_resolution;
  angular_resolution_reciprocal_ = 1.0f / angular_resolution_;
}

}  // namespace end

---

pcl
Author(s): See http://pcl.ros.org/authors for the complete list of authors.
autogenerated on Fri Jan 11 09:55:23 2013