Laser scanning in engineering survey — An application study

Berenyi, Attila

doi:10.1556/pollack.5.2010.2.4

Cited by 14 publications

(9 citation statements)

References 1 publication

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“…Pollack Periodica 13, 2018, 2 accurate scanning equipment that can quickly digitize the geometry of a real-world object [1], [2], [3]. With the development of hardware, the processing of acquired data is gaining more and more attention.…”

Section: R Honti J Erdélyi a Kopáčikmentioning

confidence: 99%

Plane segmentation from point clouds

2018

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Recently, attempts have been made to automate data acquisition, which is also related to efforts to automate data processing. The paper deals with the automation of terrestrial laser scanning data processing. The approaches for point cloud segmentation are briefly described. An algorithm based on random sample consensus is proposed for automated plane identification and plane segmentation from point clouds. The proposed approach was tested by processing point clouds; the results of the testing are also described. Based on the proposed algorithm, a standalone application for automated plane segmentation from laser scanner data using Matlab ® software was developed.

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Section: R Honti J Erdélyi a Kopáčikmentioning

confidence: 99%

Plane segmentation from point clouds

2018

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“…There are more and more solutions to produce or process even 3 dimensional data [6], [7]. The Light Detection and Ranging (LiDAR) data basis is one of the most significant sources, which can be effectively applied in several engineer applications [8], for example creating 3D city models or even estimate solar energy production based on roof models [9]. The Airborne Laser Scanning (ALS) created the possibility of gathering high resolution elevation data and deriving precise DTMs.…”

Section: A Juhász H Neubergermentioning

confidence: 99%

Automatic selection of potential WWII bombed areas by using spatial data

Juhász

Neuberger

2018

Pollack Periodica

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The reconstruction of military defense systems, (e.g. World War II defense lines) is generally based on military object identification and mapping. Since unexploded bombs can be still dangerous today, detecting bomb craters can be useful in creating hazard maps. The most significant problem is managing the large amount of relevant data. Therefore, there is a strong demand for automatically select the potential danger zones and also automate the entire processing workflow. Automatic methods have been developed to reduce the areas of interest. In addition, this method can be applied in other tasks as well, for example in settlement detection.

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“…Comparing the sparse and dense point clouds for the same methods, it is noticeable that the former ones are more affected by errors. There is one exception; due to the extreme computational requirements, the input image resolution for the COLMAP's densification had to be reduced significantly [29], [30].…”

Section: The Comparison Of the Derived Point Cloudsmentioning

confidence: 99%

Comparison of spatial reconstruction software packages using DSLR images

2017

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Point cloud based modeling has become widely used in recent years in the engineering practice. This paper presents several point clouds produced by different software packages using pixel based multi view spatial reconstruction. The purpose of the investigation is to give statistical quality measures beyond the apparent differences between the point clouds. Reference measurements have been carried out by terrestrial laser scanning. There are proprietary and free software solutions among the tested programs.

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Laser scanning in engineering survey — An application study

Cited by 14 publications

References 1 publication

Plane segmentation from point clouds

Plane segmentation from point clouds

Automatic selection of potential WWII bombed areas by using spatial data

Comparison of spatial reconstruction software packages using DSLR images

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