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Affiliation of Author(s):机电学院

Journal:ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Key Words:LiDAR point cloud Electrical substation scene Automatic 3D reconstruction Pattern detection Shape retrieval

Abstract:3D reconstruction of a large-scale electrical substation scene (ESS) is fundamental to navigation, information inquiry, and supervisory control of 3D scenes. However, automatic reconstruction of ESS from a raw LiDAR point cloud is challenging due to its incompleteness, noise and anisotropy in density. We propose an automatic and efficient approach to reconstruct ESSs, by mapping raw LiDAR data to our well-established electrical device database (EDD). We derive a flexible and hierarchical representation of the ESS automatically by exploring the internal topology of the corresponding LiDAR data, followed by extracting various devices from the ESS. For each device, a quality mesh model is retrieved in the EDD, based on the proposed object descriptor that can balance descriptiveness, robustness and efficiency. With the high-level representation of the ESS, we map all retrieved models into raw data to achieve a high-fidelity scene reconstruction. Extensive experiments on large and complex ESSs modeling demonstrate the efficiency and accuracy of the proposed method.

ISSN No.:0924-2716

Translation or Not:no

Date of Publication:2018-09-01

Co-author:wuqiaoyun,杨鸿斌,Remil, Oussama,Wang, Bo,Jun Wang

Correspondence Author:Jun Wang,Mingqiang Wei