CHATGPT FOR POINT CLOUD 3D OBJECT PROCESSING
Large-scale pretrained language models have been a revolution in human-machine communication. Recently, such language models also generate code for required tasks. The objective of this work is to evaluate the functionality of the codes generated by ChatGPT (version 15-Dec-2022) for point cloud proc...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-12-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-annals.copernicus.org/articles/X-1-W1-2023/107/2023/isprs-annals-X-1-W1-2023-107-2023.pdf |
| _version_ | 1797403810065285120 |
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| author | J. Balado G. Nguyen |
| author_facet | J. Balado G. Nguyen |
| author_sort | J. Balado |
| collection | DOAJ |
| description | Large-scale pretrained language models have been a revolution in human-machine communication. Recently, such language models also generate code for required tasks. The objective of this work is to evaluate the functionality of the codes generated by ChatGPT (version 15-Dec-2022) for point cloud processing. The programming language selected for the test was MATLAB due to the extensive use in prototyping and toolboxes for Computer Vision and LiDAR. Using the Question-Answer system, the ChatGPT was asked for codes to calculate surface normals, curvature, eigenvalues, and eigenfeatures, with specific parameters and outputs. The provided codes were compiled and executed. The results show that ChatGPT can generate functional code for very specific and short applications, however, it is not capable of generating large code involving the correct use of loops, indexes, or equations. |
| first_indexed | 2024-03-09T02:43:47Z |
| format | Article |
| id | doaj.art-eec8e3691869421aaad6f47c71941f77 |
| institution | Directory Open Access Journal |
| issn | 2194-9042 2194-9050 |
| language | English |
| last_indexed | 2024-03-09T02:43:47Z |
| publishDate | 2023-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-eec8e3691869421aaad6f47c71941f772023-12-05T23:26:12ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502023-12-01X-1-W1-202310711410.5194/isprs-annals-X-1-W1-2023-107-2023CHATGPT FOR POINT CLOUD 3D OBJECT PROCESSINGJ. Balado0G. Nguyen1GeoTECH, CINTECX, Universidade de Vigo, 36310 Vigo, SpainFaculty of Informatics and Information Technologies, Slovak University of Technology, Ilkovičova 2, Bratislava 84216, SlovakiaLarge-scale pretrained language models have been a revolution in human-machine communication. Recently, such language models also generate code for required tasks. The objective of this work is to evaluate the functionality of the codes generated by ChatGPT (version 15-Dec-2022) for point cloud processing. The programming language selected for the test was MATLAB due to the extensive use in prototyping and toolboxes for Computer Vision and LiDAR. Using the Question-Answer system, the ChatGPT was asked for codes to calculate surface normals, curvature, eigenvalues, and eigenfeatures, with specific parameters and outputs. The provided codes were compiled and executed. The results show that ChatGPT can generate functional code for very specific and short applications, however, it is not capable of generating large code involving the correct use of loops, indexes, or equations.https://isprs-annals.copernicus.org/articles/X-1-W1-2023/107/2023/isprs-annals-X-1-W1-2023-107-2023.pdf |
| spellingShingle | J. Balado G. Nguyen CHATGPT FOR POINT CLOUD 3D OBJECT PROCESSING ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | CHATGPT FOR POINT CLOUD 3D OBJECT PROCESSING |
| title_full | CHATGPT FOR POINT CLOUD 3D OBJECT PROCESSING |
| title_fullStr | CHATGPT FOR POINT CLOUD 3D OBJECT PROCESSING |
| title_full_unstemmed | CHATGPT FOR POINT CLOUD 3D OBJECT PROCESSING |
| title_short | CHATGPT FOR POINT CLOUD 3D OBJECT PROCESSING |
| title_sort | chatgpt for point cloud 3d object processing |
| url | https://isprs-annals.copernicus.org/articles/X-1-W1-2023/107/2023/isprs-annals-X-1-W1-2023-107-2023.pdf |
| work_keys_str_mv | AT jbalado chatgptforpointcloud3dobjectprocessing AT gnguyen chatgptforpointcloud3dobjectprocessing |