Research on Pole Shaped Feature Extraction Method Based on Vehicle Laser Scanning Point Cloud Data
As an important public facility in road scenes,it is particularly important to study how to automatically and accurately classi-fy pole shaped objects.This article proposes a clustering based automatic extraction method for pole shaped objects based on vehicle-borne laser scanning point cloud data.The main implementation steps are as follows:first,it projects the original road vehicle-borne laser point cloud data horizontally and constructs a grid,and extracts ground points on a grid basis;secondly,it conducts clustering of ground points based on grid;finally,it uses a single point cloud block from the clustering results as the processing unit,fine extraction and classification of pole shaped objects are achieved based on the spatial expression characteristics of the features.In order to verify the effectiveness of the proposed pole shaped object method in this article,experimental results were conducted using measured road point cloud data,and the results of pole shaped object extraction were compared with those of manual extraction.The results showed that both lamp poles and roadside trees achieved high detection rates,proving the correctness and superiority of the algorithm.
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