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, vol.8, pp.38-59, 2020 (SCI-Expanded, Scopus)

  • Publication Type: Article / Article
  • Volume: 8
  • Publication Date: 2020
  • Doi Number: 10.1109/mgrs.2019.2937630
  • Journal Name: IEEE Geoscience and Remote Sensing Magazine
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, Geobase
  • Page Numbers: pp.38-59
  • Keywords: 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
  • Open Archive Collection: AVESIS Open Access Collection
  • Karadeniz Technical University Affiliated: No

Abstract

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.