README

본 장에서는 PCL에서 제공하는 기능들을 기반으로 Clustering, Classification, Octree, Registration를 다루고 있습니다.

• 군집화 : DBSCAN, seed Clustering

• 포인트 탐색과 배경제거 : Octree Search, Octree compress

• 특징(Feature) 찾 : Normal

• 학습/분류 : SVM

• 정합 : ICP

• 재구성: Smoothing, Triangulation

• 군집화 (70%)

  • Euclidean-PCL-Cpp (70%)

  • Euclidean-PCL-Python (0%)

  • Conditional-Euclidean-PCL-Cpp (50%)

  • DBSCAN-PCL-Python (0%)

  • Region-Growing-PCL-Cpp (50%)

  • Region-Growing-RGB-PCL-Cpp (50%)

  • Min-Cut-PCL-Cpp (50%)

  • Model-Outlier-Removal-PCL-Cpp (50%)

  • Progressive-Morphological-Filter-PCL-Cpp (50%)

• 포인트 탐색과 배경제거 (60%)

  • Search-Octree-PCL-Cpp (70%)

  • Search-Octree-PCL-Python (70%)

  • Search-Kdtree-PCL-Cpp (70%)

  • Search-Kdtree-PCL-Python (70%)

  • Compression-PCL-Cpp (70%)

  • DetectChanges-PCL-Cpp (50%)

  • DetectChanges-PCL-Python (50%)

• 특징 찾기 (50%)

  • Normal-PCL-Cpp (70%)

  • Normal-PCL-Python (80%)

• 분류 (30%)

  • SVM-RGBD-PCL-Python (70%)

  • SVM-LIDAR-PCL-Python (0%)

  • SVM-ROS (0%)

• 정합 (70%)

  • ICP-PCL-Cpp (70%)

  • ICP-ROS 실습 (10%)

• 재구성 (30%)

  • Smoothig-PCL-Cpp (70%)

  • Smoothig-PCL-Python (70%)

  • Triangulation-PCL-Cpp (70%)