capacity

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

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

* Preallocate spaces for vertices * @param num_vertices */

* Return the hat map of the provided vector (a skew symmetric matrix). * @param u 3-by-1 vector * @param x 3-by-3 skew symmetric matrix */

* @brief Default constructor for PointCloud */

* Return true if the vertex exists. * @param vertex * @return */

* Get the number of edges * @return total number of edges */

* Get the number of vertices * @return total number of vertices */

* Add a vertex with no edges. * @param [in] id the id of vertex to be added */

Create a list of spheres from a 2D numpy array Numpy array needs to be N-by-3

* A helper function to generate mock input for testing PMC code * @return a mock input to PMC max clique functions */

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

* Print adjacency matrix given a bool** * @param adj a bool** to the adjcency matrix * @param nodes number of nodes in the graph */

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

* Return inliers from rotation estimation * * @return a vector of indices of measurements deemed as inliers by rotation estimation */

* Return the index map for translation inliers (equivalent to max clique). * * @return a 1-by-(size of max clique) Eigen matrix. Entries represe

* Convert a 3-by-N mxArray to Eigen 3-by-N matrix * @param pa */

* Get immediate subdirectories' names as strings in a vector * @param path path to the root directory * @return a vector containing names of the imm

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

Aligns vector a to vector b with axis angle rotation

Use TEASER++ to perform global registration

Use kdtree to find mutually closest keypoints ref_key: reference keypoints (source) test_key: test keypoints (target) ref: referenc

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

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

* Return inliers from rotation estimation * * @return a vector of indices of TIMs passed to rotation estimator deemed as inliers by rotation

* Return a boolean Eigen row vector indicating whether specific measurements are inliers * according to the rotation solver. * * @return a 1-

* Return inlier TIMs from scale estimation * * @return a vector of tuples. Entries in each tuple represent the indices of * the two measureme

* Return the index map for scale inliers (equivalent to the index map for TIMs). * * @return a 2-by-(number of TIMs) Eigen matrix. Entries in on

* Return a boolean Eigen row vector indicating whether specific measurements are inliers * according to scales. * * @return a 1-by-(number of

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

Get angular error

Calculate angular error

* Return true if said edge exists * @param [in] vertex_1 * @param [in] vertex_2 */

Normalizes a numpy array of points

Heper funtion for evaluating a pair in a scene Helper function for investigating matches between pairs

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

* Set the scale estimator used * @param estimator */

Helper function for visualizing the correspondences target is fragment1 source is fragment2

* Remove default constructor */

New methods Public methods: 1. calculateCorrespondences input: source point cloud, target point cloud output: correspondences

* @brief Default constructor */

* @brief Default constructor */

* Python interface with pybind11 */