Automatic 3D reconstruction of electrical substation scene from LiDAR point cloud

IF 10.6 1区 地球科学 Q1 GEOGRAPHY, PHYSICAL
Qiaoyun Wu , Hongbin Yang , Mingqiang Wei , Oussama Remil , Bo Wang , Jun Wang
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引用次数: 21

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.

基于LiDAR点云的变电站场景自动三维重建
大型变电站场景的三维重建是三维场景导航、信息查询和监控的基础。然而,由于ESS的不完整性、噪声和密度各向异性,从原始激光雷达点云自动重建ESS具有挑战性。我们提出了一种自动有效的重建ESS的方法,通过将原始激光雷达数据映射到我们完善的电气设备数据库(EDD)。我们通过探索相应激光雷达数据的内部拓扑结构,然后从ESS中提取各种设备,自动推导出ESS的灵活分层表示。对于每个设备,基于所提出的可以平衡描述性、鲁棒性和效率的对象描述符,在EDD中检索质量网格模型。通过ESS的高级表示,我们将所有检索到的模型映射到原始数据中,以实现高保真场景重建。在大型复杂ESSs建模上的大量实验证明了该方法的有效性和准确性。
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来源期刊
ISPRS Journal of Photogrammetry and Remote Sensing
ISPRS Journal of Photogrammetry and Remote Sensing 工程技术-成像科学与照相技术
CiteScore
21.00
自引率
6.30%
发文量
273
审稿时长
40 days
期刊介绍: The ISPRS Journal of Photogrammetry and Remote Sensing (P&RS) serves as the official journal of the International Society for Photogrammetry and Remote Sensing (ISPRS). It acts as a platform for scientists and professionals worldwide who are involved in various disciplines that utilize photogrammetry, remote sensing, spatial information systems, computer vision, and related fields. The journal aims to facilitate communication and dissemination of advancements in these disciplines, while also acting as a comprehensive source of reference and archive. P&RS endeavors to publish high-quality, peer-reviewed research papers that are preferably original and have not been published before. These papers can cover scientific/research, technological development, or application/practical aspects. Additionally, the journal welcomes papers that are based on presentations from ISPRS meetings, as long as they are considered significant contributions to the aforementioned fields. In particular, P&RS encourages the submission of papers that are of broad scientific interest, showcase innovative applications (especially in emerging fields), have an interdisciplinary focus, discuss topics that have received limited attention in P&RS or related journals, or explore new directions in scientific or professional realms. It is preferred that theoretical papers include practical applications, while papers focusing on systems and applications should include a theoretical background.
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