2019
DOI: 10.1007/978-3-030-10374-3_2
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Road Geometric Modeling Using Laser Scanning Data: A Critical Review

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Cited by 3 publications
(2 citation statements)
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“…1 In this paper, we follow the principle of minimizing point cloud errors by implementing a fine stitching process for data acquisition. [13] 2 Relying on the 3D laser scanner, by collecting the data of the target 3D point cloud as the basis, the point cloud data model proposed in this paper improves the resolution for both image and accuracy, and enriches the diversity of product service types. [11] LiDAR, the classification and domain of point cloud data are discussed and analyzed, and several common point cloud domains finding methods are reviewed.…”
Section: Feature-based Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…1 In this paper, we follow the principle of minimizing point cloud errors by implementing a fine stitching process for data acquisition. [13] 2 Relying on the 3D laser scanner, by collecting the data of the target 3D point cloud as the basis, the point cloud data model proposed in this paper improves the resolution for both image and accuracy, and enriches the diversity of product service types. [11] LiDAR, the classification and domain of point cloud data are discussed and analyzed, and several common point cloud domains finding methods are reviewed.…”
Section: Feature-based Methodsmentioning
confidence: 99%
“…The motivation behind this research is to address the limitations and gaps in current point cloud data processing methods. By understanding and evaluating state-of-the-art techniques, we aim to foster the development of advanced algorithms and tools to enhance the accuracy, robustness, and automation of point cloud data processing (Pradhan & Sameen, 2021). Furthermore, the potential applications of these techniques in fields such as architecture, civil engineering, cultural heritage preservation, and virtual reality underscore the importance of this research.…”
Section: Introductionmentioning
confidence: 99%