DETECTION AND CLASSIFICATION OF POLE-LIKE OBJECTS FROM MOBILE MAPPING DATA

DETECTION AND CLASSIFICATION OF POLE-LIKE OBJECTS FROM MOBILE MAPPING DATA

Blog Article

Laser scanners on a vehicle-based mobile mapping system can capture 3D point-clouds of roads and roadside objects.Since roadside objects have to be maintained periodically, their 3D models are useful for planning maintenance tasks.In our previous work, we proposed a method for detecting cylindrical poles and planar plates in a point-cloud.However, it is often required to further classify pole-like objects into utility poles, streetlights, traffic signals and signs, which are managed by different organizations.In addition, our previous method may fail to extract low pole-like objects, which are often click here observed in urban residential areas.

In this paper, we propose new methods for extracting and classifying pole-like objects.In our method, we robustly extract a wide variety of poles by converting point-clouds into wireframe models and calculating cross-sections between wireframe models and horizontal cutting planes.For classifying pole-like objects, we subdivide a pole-like object into five subsets by extracting poles and planes, lycogel and calculate feature values of each subset.Then we apply a supervised machine learning method using feature variables of subsets.In our experiments, our method could achieve excellent results for detection and classification of pole-like objects.