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minimal util3d_surface.h

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matlabbe
2025-07-06 12:02:09 -07:00
parent d558c3a93b
commit b8d253129c
3 changed files with 169 additions and 1 deletions
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corelib/include/rtabmap/core/util3d_surface.h
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@@ -395,29 +395,73 @@ pcl::PointCloud<pcl::Normal>::Ptr RTABMAP_CORE_EXPORT computeFastOrganizedNormal
float normalSmoothingSize = 10.0f,
const Eigen::Vector3f & viewPoint = Eigen::Vector3f(0,0,0));
/**
* @defgroup ComputeNormalsComplexity Compute Structural Complexity of a Point Cloud with Normals
* @brief Computes the complexity of surface normals in a point cloud using PCA.
*
* This function performs a Principal Component Analysis (PCA) on the normals of a point cloud
* and returns a scalar measure of their spread (complexity). A low value indicates that normals
* are aligned (e.g., flat surface), while a high value indicates variation in orientation (e.g., curved or rough surface).
*
* If a transformation is provided, the normals are rotated accordingly before PCA. The result is normalized
* to lie between 0 and 0.25, where 0 represents minimal complexity and 0.25 represents maximal complexity.
*
* @param cloud The input point cloud or laser scan containing normals (pcl::PointNormal), or simply normals.
* @param t The transform to apply to the normals (only the rotation is used).
* @param is2d Set to true if the data is 2D (normals will be analyzed in 2D space).
* @param pcaEigenVectors (Optional) Output matrix containing the eigenvectors computed by PCA.
* @param pcaEigenValues (Optional) Output matrix containing the eigenvalues computed by PCA.
*
* @return A float value between 0 and 0.25 representing the complexity of the normal distribution.
* Returns 0 if not enough valid normals are available.
*
* @note Invalid normals (containing NaN or Inf) are automatically filtered out.
* The result is based on the smallest eigenvalue from PCA (for 2D: 2nd eigenvalue, for 3D: 3rd eigenvalue).
*
*/
/**
* @ingroup ComputeNormalsComplexity
* @brief Computes the complexity of surface normals in a point cloud of type `LaserScan`.
*/
float RTABMAP_CORE_EXPORT computeNormalsComplexity(
const LaserScan & scan,
const Transform & t = Transform::getIdentity(),
cv::Mat * pcaEigenVectors = 0,
cv::Mat * pcaEigenValues = 0);
/**
* @ingroup ComputeNormalsComplexity
* @brief Computes the complexity of surface normals in a point cloud of type `pcl::Normal`.
*/
float RTABMAP_CORE_EXPORT computeNormalsComplexity(
const pcl::PointCloud<pcl::Normal> & normals,
const Transform & t = Transform::getIdentity(),
bool is2d = false,
cv::Mat * pcaEigenVectors = 0,
cv::Mat * pcaEigenValues = 0);
/**
* @ingroup ComputeNormalsComplexity
* @brief Computes the complexity of surface normals in a point cloud of type `pcl::PointNormal`.
*/
float RTABMAP_CORE_EXPORT computeNormalsComplexity(
const pcl::PointCloud<pcl::PointNormal> & cloud,
const Transform & t = Transform::getIdentity(),
bool is2d = false,
cv::Mat * pcaEigenVectors = 0,
cv::Mat * pcaEigenValues = 0);
/**
* @ingroup ComputeNormalsComplexity
* @brief Computes the complexity of surface normals in a point cloud of type `pcl::PointXYZINormal`.
*/
float RTABMAP_CORE_EXPORT computeNormalsComplexity(
const pcl::PointCloud<pcl::PointXYZINormal> & cloud,
const Transform & t = Transform::getIdentity(),
bool is2d = false,
cv::Mat * pcaEigenVectors = 0,
cv::Mat * pcaEigenValues = 0);
/**
* @ingroup ComputeNormalsComplexity
* @brief Computes the complexity of surface normals in a point cloud of type `pcl::PointXYZRGBNormal`.
*/
float RTABMAP_CORE_EXPORT computeNormalsComplexity(
const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud,
const Transform & t = Transform::getIdentity(),