capacity

* Clear the contents of the graph */

* Preallocate spaces for vertices * @param num_vertices */

Returns the dim'th component of the idx'th point in the class:

Helper accessor to the dataset points:

* Return a boolean Eigen row vector indicating whether specific * measurements are inliers according to translation measurements. * @return

* Return the solution to the registration problem. * @return */

Must return the number of data points

* Reset the solver using the provided params * @param params a Params struct */

* Builds the index */

* @brief Compute centroid and covariance matrix for every cluster center * * @param cluster_centroid output cluster centers with semantic

Frees the previously-built index. Automatically called within * buildIndex(). */

following code for dynamic voxel segmentation

* Add an edge between two vertices * @param [in] vertex_1 one vertex of the edge * @param [in] vertex_2 another vertex of the edge */

* Called during search to add an element matching the criteria. * @return true if the search should be continued, false if the results are * suf

template <typename T>

* Create a tree node that subdivides the list of vecs from vind[first] * to vind[last]. The routine is called recursively on each sublist. *

Loads a previous index from a binary file. * IMPORTANT NOTE: The set of data points is NOT stored in the file, so the * index object must be c

* Populate the graph with the provided number of vertices without any edges. * @param num_vertices */

Stores the index in a binary file. * IMPORTANT NOTE: The set of data points is NOT stored in the file, so when * loading the index object it m

* SO3 expmap code taken from Sophus * https://github.com/strasdat/Sophus/blob/593db47500ea1a2de5f0e6579c86147991509c59/sophus/so3.hpp#L585 * * Copy

* Helper function to use svd to estimate rotation. * Method described here: http://igl.ethz.ch/projects/ARAP/svd_rot.pdf * @param X * @param Y * @

* @brief Color point cloud according to per point semantic labels. * @param[in] semantic_cloud: input semantic cloud ptr (with label) * @param

toy definition for scale involved case

Frees all allocated memory chunks */

* Return the cost of the GNC solver at termination. Details of the cost * function is dependent on the specific solver implementation. *

* Get all vertices * @return a vector of all vertices */

* Find the "num_closest" nearest neighbors to the \a query_point[0:dim-1]. * Their indices are stored inside the result object. \sa radiusSearch,

* Returns a pointer to a piece of new memory of the given size in bytes * allocated from the pool. */

* @brief Merge cloud and label to semantic_pc. * @param[in] label_file_path; raw_point_cloud; out_semantic_pc * @return None. */

* @brief read the covariance vector of a point cloud from the file * * @param fin input stream of the file been opened * @param matrix_vector covar