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

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

* Find the "num_closest" nearest neighbors to the \a query_point[0:dim-1]. * Their indices and distances are stored in the provided pointers

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

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

* @brief Given a R3 vector (v1), calculate two orthogonal vectors (v2 and v3) to * form a orthogonal basis * @param normal * Vecto

Method to prune the graph safely

* Find all the neighbors to \a query_point[0:dim-1] within a maximum * radius. The output is given as a vector of pairs, of which the first

following code for dynamic voxel segmentation

We have to load the machine type from the image info So we first initialize the resolver, and it tells us this info

Types are resolved from right to left: we get the variable name first and then all specifiers (like const or pointer) in a chain of DW_AT_type DIEs. C

Split a string on the platform's PATH delimiter. Example: if delimiter is ":" then: "" --> [] ":" --> ["",""] "::"

* @brief the Dynamic Curved-Voxle Clustering algoithm for fast and precise point cloud segmentaiton * @param label_info, output the category info

typedef boost::shared_ptr<pcl::PointCloud<PointT>> PointCloudPtr;

* Remove default constructor */

finds position of least significant unset bit */