Automatic Detection and Classification of Pole-Like Objects in Urban Point Cloud Data Using an Anomaly Detection Algorithm

Automatic Detection and Classification of Pole-Like Objects in Urban Point Cloud Data Using an Anomaly Detection Algorithm

Detecting and modeling urban furniture are of particular interest for urban management and the development of autonomous driving systems. This paper presents a novel method for detecting and classifying vertical urban objects and trees from unstructured three-dimensional mobile laser scanner (MLS) o...

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Bibliographic Details
Main Authors: Borja Rodríguez-Cuenca, Silverio García-Cortés, Celestino Ordóñez, Maria C. Alonso
Format: Article
Language:English
Published: MDPI AG 2015-09-01
Series:Remote Sensing
Subjects:
pole-like objects
feature extraction
pattern recognition
clustering
3D point cloud
MLS
anomaly detection
Online Access:http://www.mdpi.com/2072-4292/7/10/12680

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