Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation

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Xie Y., TIAN J., Zhu X.

IEEE Geoscience and Remote Sensing Magazine, cilt.8, ss.38-59, 2020 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 8
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1109/mgrs.2019.2937630
  • Dergi Adı: IEEE Geoscience and Remote Sensing Magazine
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, Geobase
  • Sayfa Sayıları: ss.38-59
  • Anahtar Kelimeler: Three-dimensional displays, Laser radar, Sensors, Synthetic aperture radar, Semantics, Cameras, Image segmentation, HOUGH TRANSFORM, CONTEXTUAL CLASSIFICATION, SUPERVOXEL SEGMENTATION, OPTIMIZATION APPROACH, INDIVIDUAL TREES, MEAN SHIFT, UAV-LIDAR, RECONSTRUCTION, FOREST, EXTRACTION
  • Karadeniz Teknik Üniversitesi Adresli: Hayır

Özet

Ripe with possibilities offered by deep-learning techniques and useful in applications related to remote sensing, computer vision, and robotics, 3D point cloud semantic segmentation (PCSS) and point cloud segmentation (PCS) are attracting increasing interest. This article summarizes available data sets and relevant studies on recent developments in PCSS and PCS.