Automatic lane marking extraction from point cloud into polygon map layer
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F19%3A43914326" target="_blank" >RIV/62156489:43110/19:43914326 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26210/18:PU130002
Result on the web
<a href="https://doi.org/10.1080/22797254.2018.1535837" target="_blank" >https://doi.org/10.1080/22797254.2018.1535837</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/22797254.2018.1535837" target="_blank" >10.1080/22797254.2018.1535837</a>
Alternative languages
Result language
angličtina
Original language name
Automatic lane marking extraction from point cloud into polygon map layer
Original language description
Optimization of road networks is a common concern worldwide, primarily for safety purposes. Because the extent of these networks is substantial, automation of their inventory is highly desirable. This paper concentrates on the road inventory process that is necessary for regular maintenance. The key part of our road marking detection and reconstruction is based on spanning tree usage. The spanning trees are obtained from alpha shapes of the detected road markings. The spanning trees application enables the reliable identification of the road markings and precise reconstruction of their contours even with noisy data. Our method processes the point cloud data obtained from LiDAR measurements, and provides a common vector layer with road lane polygons. Such a vector layer is stored in a common file format supported by the majority of geographical information systems, thus producing an output that can be conveniently used for decision-making based on the road inventory process.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
European Journal of Remote Sensing
ISSN
2279-7254
e-ISSN
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Volume of the periodical
52
Issue of the periodical within the volume
S1
Country of publishing house
IT - ITALY
Number of pages
14
Pages from-to
26-39
UT code for WoS article
000475928900004
EID of the result in the Scopus database
2-s2.0-85055685908