GitLab

 * This approach describes the surface detection of Zahra Lari and Ayman Habib (2014).
 * Paper: "An adaptive approach for the segmentation and extraction of planar
 * andlinear/cylindrical features from laser scanning data", ISPRS Journal of
 * Photogrammetry and Remote Sensing, 2014
 *
 * Eventually the process covers also the linear and cylindrical feature segmentation
 * but in our requirements only the planar segmentation is required. Steps:
 *   - Original laser point cloud as input data
 *   - PCA-based classification of planar features
 *   - Selection of appropriate representation models for the detected planar features
 *   - Local point density estimation along the detected planar features
 *   - Precise estimation of the planar features segmentation attributes
 *   - Parameter-domain segmentation and extraction of planar features
 *   - Boundary tracking for resolving the parameter-domain segmentation ambiguities of
 *     planar features
 *   - Extracted planar features in spatial domain
 *
 * Estimations (Based on the paper because I haven't completely impelemented yet):
 *   - Fair segmentation results
 *   - Relatively slow
 *
 * Implementation progress:
 *   - Done to the step "Precise estimation of the planar features segmentation
 *     attributes".
 *
 *
 * Other updates:
 *   - Renamed module "Pooints - Crop" to "Points - Transform". It optained the feature
 *     to translate and to rotate the point set.
 *   - Wew code refactoring.