Modeling and analysis of light detection and ranging point cloud error in vibration state of airborne platform

Lin, Zhaodong; Chen, Xiong; Di, Changán; Yu, Jirong; Peng, Peng; Yu, Chengtao

doi:10.1117/1.oe.61.2.024103

Cited by 1 publication

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“…In order to obtain the complete 3D laser point cloud data, the following layout principles of 3D laser scanners should be followed: First, through on-the-spot reconnaissance, the operation scope should be arranged according to the topographic features and features of the survey area, and scanning stations should be arranged, and the positions of scanning instruments should be reasonably arranged to ensure that the data of adjacent stations have overlapping parts [13]. At the same time, the number of stations should be reduced as much as possible, so as to reduce the amount of data and the splicing error before the stations.…”

Section: Laser Point Cloud Big Data Collection In Building Spacementioning

confidence: 99%

Visual reconstruction method of architectural space under laser point cloud big data

Ma,

2024

J. meas. eng.

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In order to solve the problem that the reconstruction accuracy and integrity are affected due to the large amount of point cloud data in the process of building space reconstruction, the visual reconstruction method of building space under laser point cloud big data is studied. The three-dimensional laser scanner is used to collect the laser point cloud big data in the building space, and the laser point cloud big data is organized and processed through three steps: hierarchical calculation of the point cloud pyramid, thinning treatment and block treatment. From the processing results of laser point cloud big data, the line features of building space are extracted based on the improved Mean-shift method, and the continuous broken lines in the point cloud data of building space are extracted by using the double radius threshold line tracing method. According to the feature extraction results of point cloud data in building space, the visual reconstruction of building space is completed through the process of translation matching and space matching. The experimental results show that this method can realize the visual reconstruction of architectural space, and the average reconstruction accuracy is higher than that of 97 %, and the reconstruction completion and smoothness are higher than 95 %.

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Section: Laser Point Cloud Big Data Collection In Building Spacementioning

confidence: 99%

Visual reconstruction method of architectural space under laser point cloud big data

Ma,

2024

J. meas. eng.

View full text Add to dashboard Cite

show abstract

Modeling and analysis of light detection and ranging point cloud error in vibration state of airborne platform

Cited by 1 publication

References 0 publications

Visual reconstruction method of architectural space under laser point cloud big data

Visual reconstruction method of architectural space under laser point cloud big data

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