Higher-Order Conditional Random Fields-Based 3D Semantic Labeling of Airborne Laser-Scanning Point Clouds

Higher-Order Conditional Random Fields-Based 3D Semantic Labeling of Airborne Laser-Scanning Point Clouds

This paper presents a novel framework to achieve 3D semantic labeling of objects (e.g., trees, buildings, and vehicles) from airborne laser-scanning point clouds. To this end, we propose a framework which consists of hierarchical clustering and higher-order conditional random fields (CRF) labeling....

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Bibliographic Details
Main Authors: Yong Li, Dong Chen, Xiance Du, Shaobo Xia, Yuliang Wang, Sheng Xu, Qiang Yang
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Remote Sensing
Subjects:
airborne laser-scanning
segmentation
cluster classification
neighborhood topology
higher-order potential
CRF optimization
Online Access:https://www.mdpi.com/2072-4292/11/10/1248

Internet

https://www.mdpi.com/2072-4292/11/10/1248

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