| 25 | |
| 26 | |
| 27 | Map* reconstruct( |
| 28 | PointSet *point_cloud, // input point cloud |
| 29 | LinearProgramSolver::SolverName solver, // solver name |
| 30 | float data_fitting, // weight for data fitting term |
| 31 | float model_coverage, // weight for model coverage term |
| 32 | float model_complexity // weight for model complexity term |
| 33 | ) |
| 34 | { |
| 35 | // step 1: refine planes |
| 36 | const std::vector<VertexGroup::Ptr>& groups = point_cloud->groups(); |
| 37 | if (groups.empty()) { |
| 38 | std::cerr << "planar segments do not exist" << std::endl; |
| 39 | return nullptr; |
| 40 | } |
| 41 | HypothesisGenerator hypothesis(point_cloud); |
| 42 | hypothesis.refine_planes(); |
| 43 | |
| 44 | // step 2: generate face hypothesis |
| 45 | Map* mesh = hypothesis.generate(); |
| 46 | if (!mesh) { |
| 47 | std::cerr << "failed generating candidate faces. Please check if the input point cloud has good planar segments" << std::endl; |
| 48 | return nullptr; |
| 49 | } |
| 50 | hypothesis.compute_confidences(mesh, false); |
| 51 | |
| 52 | // step 3: face selection |
| 53 | FaceSelection selector(point_cloud, mesh); |
| 54 | selector.optimize(&hypothesis, solver, data_fitting, model_coverage, model_complexity); |
| 55 | |
| 56 | if (mesh->size_of_facets() == 0) { |
| 57 | std::cerr << "optimization failed: result has no face" << std::endl; |
| 58 | return nullptr; |
| 59 | } |
| 60 | // now we don't need the point cloud anymore, and it can be deleted |
| 61 | return mesh; |
| 62 | } |
| 63 |
no test coverage detected