\brief Get child pointer in current branch node * \param buffer_arg: buffer selector, must be less than 2 * \param index_arg: index of child i

\brief Make this and 'node' neighbors by inserting each node in the others node neighbor set. Nothing happens * of either of the nodes h

\brief Set the maximum distance threshold between two correspondent points in * source <-> target. If the distance is larger than this threshold, t

\brief Set the transformation epsilon (maximum allowable translation squared * difference between two consecutive transformations) in order for an

///////////////////////////////////////////////////////////////////////////////////////////////////////////// Handle Ensenso SDK exceptions This funct

\brief check if current node is a branch node * \return true if current node is a branch node, false otherwise */

////////////////////////////////////////////////////////////////////////////////////////

/////////////////////////////////////////////////////////////////////////////////////////

\brief Get the maximum depth of the octree. * \return depth_arg: maximum depth of octree */

/////////////////////////////////////////////////////////////////////////////////////////

\brief Set the sphere radius that is to be used for determining the k-nearest neighbors used for fitting. * \param[in] radius the sphere radiu

\brief Get the current octree node * \return pointer to current octree node */

\brief Returns the height of the map. */

\brief Returns the width of the map. */

/////////////////////////////////////////////////////////////////////////////////////////

\brief Resize the internal point data vectors. * \param newsize the new size */

///// If the intersection is not empty, then intersection = [max(this.Min(),arg.Min()), min(this.Max(),arg.Max())] Intersection() returns true if the

/////////////////////////////////////////////////////////////////////////////////////////////////////////////////

/////////////////////////////////////////////////////////////////////////////////////////////////////////////////

Return the current training parameters. */

@brief Search for the k-nearest neighbors for the given query point. * @param[in] point the given query point * @param[in] k the number of neigh

/////////////////////////////////////////////////////////////////////////////////////////

\brief Set to true if all fields need to be downsampled, or false if just XYZ. * \param downsample the new value (true/false) */

//////////////////////////////////////////////////////////////////////////////////

\brief Clear the graph */

////////////////////////////////////////////////////////////////////////////////////////

\brief Get the voxel centroid. * \return centroid */

\brief Get a pointer to the model coefficients. */

\brief Returns if a point X is visible from point R (or the origin) * when taking into account the segment between the points S1 and S2 * \par

////////////////////////////////////////////////////////////////////////////////////////

\brief Set the normal smoothing size * \param[in] normal_smoothing_size factor which influences the size of the area used to smooth normals