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Algorithms of laser scanner data processing for ground surface reconstruction. / Баденко, Владимир Львович; Виноградов, Константин Павлович; Федотов, Александр.

в: Lecture Notes in Computer Science, Том 10961 LNCS, 01.10.2018, стр. 397-411.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Баденко, ВЛ, Виноградов, КП & Федотов, А 2018, 'Algorithms of laser scanner data processing for ground surface reconstruction', Lecture Notes in Computer Science, Том. 10961 LNCS, стр. 397-411. https://doi.org/10.1007/978-3-319-95165-2_28

APA

Баденко, В. Л., Виноградов, К. П., & Федотов, А. (2018). Algorithms of laser scanner data processing for ground surface reconstruction. Lecture Notes in Computer Science, 10961 LNCS, 397-411. https://doi.org/10.1007/978-3-319-95165-2_28

Vancouver

Баденко ВЛ, Виноградов КП, Федотов А. Algorithms of laser scanner data processing for ground surface reconstruction. Lecture Notes in Computer Science. 2018 Окт. 1;10961 LNCS:397-411. https://doi.org/10.1007/978-3-319-95165-2_28

Author

Баденко, Владимир Львович ; Виноградов, Константин Павлович ; Федотов, Александр. / Algorithms of laser scanner data processing for ground surface reconstruction. в: Lecture Notes in Computer Science. 2018 ; Том 10961 LNCS. стр. 397-411.

BibTeX

@article{c6b55b26500041a5abbe71792362921c,
title = "Algorithms of laser scanner data processing for ground surface reconstruction",
abstract = "Laser scanning data processing is widely used to solve regional planning problems in a GIS environment including Digital Terrain Models (DTMs) analysis and ground surface reconstruction. Some gaps in algorithms for processing of raw laser scanning data during DTM creation are analyzed. Algorithms for filtration, triangulation and defragmentation of laser scanning point clouds are proposed. Advantages and disadvantages of the algorithms proposed are discussed. The proposed triangulation algorithm is used for defragmentation of laser scanning point clouds into semantic component parts. Defragmentation includes recognition of engineering objects and other objects of the terrain, and their delineation. The results of real problems{\textquoteright} solutions described in the paper show the robustness of the proposed algorithms",
keywords = "Algorithm, Digital Terrain Model, Ground surface reconstruction, Laser scanning data, Triangulation",
author = "Баденко, {Владимир Львович} and Виноградов, {Константин Павлович} and Александр Федотов",
note = "205. Badenko, V., Fedotov, A., Vinogradov, K. Algorithms of laser scanner data processing for ground surface reconstruction (2018) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10961 LNCS, pp. 397-411. DOI: 10.1007/978-3-319-95165-2_28",
year = "2018",
month = oct,
day = "1",
doi = "10.1007/978-3-319-95165-2_28",
language = "English",
volume = "10961 LNCS",
pages = "397--411",
journal = "Lecture Notes in Computer Science",
issn = "0302-9743",
publisher = "Springer Nature",

}

RIS

TY - JOUR

T1 - Algorithms of laser scanner data processing for ground surface reconstruction

AU - Баденко, Владимир Львович

AU - Виноградов, Константин Павлович

AU - Федотов, Александр

N1 - 205. Badenko, V., Fedotov, A., Vinogradov, K. Algorithms of laser scanner data processing for ground surface reconstruction (2018) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10961 LNCS, pp. 397-411. DOI: 10.1007/978-3-319-95165-2_28

PY - 2018/10/1

Y1 - 2018/10/1

N2 - Laser scanning data processing is widely used to solve regional planning problems in a GIS environment including Digital Terrain Models (DTMs) analysis and ground surface reconstruction. Some gaps in algorithms for processing of raw laser scanning data during DTM creation are analyzed. Algorithms for filtration, triangulation and defragmentation of laser scanning point clouds are proposed. Advantages and disadvantages of the algorithms proposed are discussed. The proposed triangulation algorithm is used for defragmentation of laser scanning point clouds into semantic component parts. Defragmentation includes recognition of engineering objects and other objects of the terrain, and their delineation. The results of real problems’ solutions described in the paper show the robustness of the proposed algorithms

AB - Laser scanning data processing is widely used to solve regional planning problems in a GIS environment including Digital Terrain Models (DTMs) analysis and ground surface reconstruction. Some gaps in algorithms for processing of raw laser scanning data during DTM creation are analyzed. Algorithms for filtration, triangulation and defragmentation of laser scanning point clouds are proposed. Advantages and disadvantages of the algorithms proposed are discussed. The proposed triangulation algorithm is used for defragmentation of laser scanning point clouds into semantic component parts. Defragmentation includes recognition of engineering objects and other objects of the terrain, and their delineation. The results of real problems’ solutions described in the paper show the robustness of the proposed algorithms

KW - Algorithm

KW - Digital Terrain Model

KW - Ground surface reconstruction

KW - Laser scanning data

KW - Triangulation

UR - http://www.scopus.com/inward/record.url?scp=85049961052&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-95165-2_28

DO - 10.1007/978-3-319-95165-2_28

M3 - Article

VL - 10961 LNCS

SP - 397

EP - 411

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

ER -

ID: 34886547