An Entropy Analysis-Based Window Size Optimization Scheme for Merging LiDAR Data Frames
LiDAR is a useful technology for gathering point cloud data from its environment and has been adapted to many applications. We use a cost-efficient LiDAR system attached to a moving object to estimate the location of the moving object using referenced linear structures. In the stationary state, the...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/23/9293 |
| _version_ | 1827642513391878144 |
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| author | Taesik Kim Jinman Jung Hong Min Young-Hoon Jung |
| author_facet | Taesik Kim Jinman Jung Hong Min Young-Hoon Jung |
| author_sort | Taesik Kim |
| collection | DOAJ |
| description | LiDAR is a useful technology for gathering point cloud data from its environment and has been adapted to many applications. We use a cost-efficient LiDAR system attached to a moving object to estimate the location of the moving object using referenced linear structures. In the stationary state, the accuracy of extracting linear structures is low given the low-cost LiDAR. We propose a merging scheme for the LiDAR data frames to improve the accuracy by using the movement of the moving object. The proposed scheme tries to find the optimal window size by means of an entropy analysis. The optimal window size is determined by finding the minimum point between the entropy indicator of the ideal result and the entropy indicator of the actual result of each window size. The proposed indicator can describe the accuracy of the entire path of the moving object at each window size using a simple single value. The experimental results show that the proposed scheme can improve the linear structure extraction accuracy. |
| first_indexed | 2024-03-09T17:32:20Z |
| format | Article |
| id | doaj.art-dfcbb9c1b93d4467b2ee49af2d5d8d12 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T17:32:20Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-dfcbb9c1b93d4467b2ee49af2d5d8d122023-11-24T12:11:49ZengMDPI AGSensors1424-82202022-11-012223929310.3390/s22239293An Entropy Analysis-Based Window Size Optimization Scheme for Merging LiDAR Data FramesTaesik Kim0Jinman Jung1Hong Min2Young-Hoon Jung3Department of Civil Engineering, Hongik University, Seoul 04066, Republic of KoreaDepartment of Computer Engineering, Inha University, Incheon 22212, Republic of KoreaSchool of Computing, Gachon University, Seongnam 13120, Republic of KoreaDepartment of Civil Engineering, Kyung Hee University, Yongin 17104, Republic of KoreaLiDAR is a useful technology for gathering point cloud data from its environment and has been adapted to many applications. We use a cost-efficient LiDAR system attached to a moving object to estimate the location of the moving object using referenced linear structures. In the stationary state, the accuracy of extracting linear structures is low given the low-cost LiDAR. We propose a merging scheme for the LiDAR data frames to improve the accuracy by using the movement of the moving object. The proposed scheme tries to find the optimal window size by means of an entropy analysis. The optimal window size is determined by finding the minimum point between the entropy indicator of the ideal result and the entropy indicator of the actual result of each window size. The proposed indicator can describe the accuracy of the entire path of the moving object at each window size using a simple single value. The experimental results show that the proposed scheme can improve the linear structure extraction accuracy.https://www.mdpi.com/1424-8220/22/23/9293LiDARentropy analysiswindow size optimizationmerging point cloud data frameslinear structure extraction |
| spellingShingle | Taesik Kim Jinman Jung Hong Min Young-Hoon Jung An Entropy Analysis-Based Window Size Optimization Scheme for Merging LiDAR Data Frames Sensors LiDAR entropy analysis window size optimization merging point cloud data frames linear structure extraction |
| title | An Entropy Analysis-Based Window Size Optimization Scheme for Merging LiDAR Data Frames |
| title_full | An Entropy Analysis-Based Window Size Optimization Scheme for Merging LiDAR Data Frames |
| title_fullStr | An Entropy Analysis-Based Window Size Optimization Scheme for Merging LiDAR Data Frames |
| title_full_unstemmed | An Entropy Analysis-Based Window Size Optimization Scheme for Merging LiDAR Data Frames |
| title_short | An Entropy Analysis-Based Window Size Optimization Scheme for Merging LiDAR Data Frames |
| title_sort | entropy analysis based window size optimization scheme for merging lidar data frames |
| topic | LiDAR entropy analysis window size optimization merging point cloud data frames linear structure extraction |
| url | https://www.mdpi.com/1424-8220/22/23/9293 |
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