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PCL点云的表示方式

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点云的表示方式

pcl里的点云多种表示方式：

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// const
ConstCloudIterator<PointT> cloud_iterator;

pcl::PointCloud<PointT> cloud;

// with indices
pcl::PointCloud<PointT> cloud;
std::vector<int> indices;

// with indices
pcl::PointCloud<PointT> cloud;
pcl::PointIndices indices;

几乎每个函数都配有这几种表示方式的 template，比如 compute3DCentroid() 会有对应的以下几种接口：

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template <typename PointT, typename Scalar> inline unsigned int
compute3DCentroid (ConstCloudIterator<PointT> &cloud_iterator,
                   Eigen::Matrix<Scalar, 4, 1> &centroid);

template <typename PointT, typename Scalar> inline unsigned int
compute3DCentroid (const pcl::PointCloud<PointT> &cloud, 
                   Eigen::Matrix<Scalar, 4, 1> &centroid);

template <typename PointT, typename Scalar> inline unsigned int
compute3DCentroid (const pcl::PointCloud<PointT> &cloud,
                   const std::vector<int> &indices, 
                   Eigen::Matrix<Scalar, 4, 1> &centroid);

template <typename PointT, typename Scalar> inline unsigned int
compute3DCentroid (const pcl::PointCloud<PointT> &cloud,
                   const pcl::PointIndices &indices, 
                   Eigen::Matrix<Scalar, 4, 1> &centroid);

在这个特定例子里，centroid 也有多种的表示方式，所以模版数量很多，看起来有些让人眼花缭乱。

但实际上，它们的实现可能非常类似。比如，对比一下点云和带 indices 点云的接口的具体实现：

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template <typename PointT, typename Scalar> inline unsigned int
compute3DCentroid (const pcl::PointCloud<PointT> &cloud,
                   Eigen::Matrix<Scalar, 4, 1> &centroid)
{
  if (cloud.empty ())
    return (0);

  // Initialize to 0
  centroid.setZero ();
  // For each point in the cloud
  // If the data is dense, we don't need to check for NaN
  if (cloud.is_dense)
  {
    for (const auto& point: cloud)
    {
      centroid[0] += point.x;
      centroid[1] += point.y;
      centroid[2] += point.z;
    }
    centroid /= static_cast<Scalar> (cloud.size ());
    centroid[3] = 1;
    return (static_cast<unsigned int> (cloud.size ()));
  }

  // NaN or Inf values could exist => check for them
  unsigned cp = 0;
  for (const auto& point: cloud)
  {
    // Check if the point is invalid
    if (!isFinite (point))
      continue;

    centroid[0] += point.x;
    centroid[1] += point.y;
    centroid[2] += point.z;
    ++cp;
  }
  centroid /= static_cast<Scalar> (cp);
  centroid[3] = 1;

  return (cp);
}
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template <typename PointT, typename Scalar> inline unsigned int
compute3DCentroid (const pcl::PointCloud<PointT> &cloud,
                   const std::vector<int> &indices,
                   Eigen::Matrix<Scalar, 4, 1> &centroid)
{
  if (indices.empty ())
    return (0);

  // Initialize to 0
  centroid.setZero ();
  // If the data is dense, we don't need to check for NaN
  if (cloud.is_dense)
  {
    for (const int& index : indices)
    {
      centroid[0] += cloud[index].x;
      centroid[1] += cloud[index].y;
      centroid[2] += cloud[index].z;
    }
    centroid /= static_cast<Scalar> (indices.size ());
    centroid[3] = 1;
    return (static_cast<unsigned int> (indices.size ()));
  }

  // NaN or Inf values could exist => check for them
  unsigned cp = 0;
  for (const int& index : indices)
  {
    // Check if the point is invalid
    if (!isFinite (cloud [index]))
      continue;

    centroid[0] += cloud[index].x;
    centroid[1] += cloud[index].y;
    centroid[2] += cloud[index].z;
    ++cp;
  }
  centroid /= static_cast<Scalar> (cp);
  centroid[3] = 1;
  return (cp);
}

很明显，只有少数的几处有区别：

  • 开头判空

    • cloud
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    if (cloud.empty()) return 0;

    • cloud with indices

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      if (indices.empty()) return 0;

  • for loop

    • cloud
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    for (const auto& point: cloud)
    {
      // point
    }

  • cloud with indices

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    for (const int& index: indices)
    {
      // cloud[index]
    }

而带 pcl::PointIndics 的接口则是直接调用了带 std::vector<int> 的接口

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template <typename PointT, typename Scalar> inline unsigned int
compute3DCentroid (const pcl::PointCloud<PointT> &cloud,
                   const std::vector<int> &indices,
                   Eigen::Matrix<Scalar, 4, 1> &centroid);

template <typename PointT, typename Scalar> inline unsigned int
compute3DCentroid (const pcl::PointCloud<PointT> &cloud,
                   const pcl::PointIndices &indices,
                   Eigen::Matrix<Scalar, 4, 1> &centroid)
{
  return (pcl::compute3DCentroid (cloud, indices.indices, centroid));
}