A Review of Optical-Based Three-Dimensional Reconstruction and Multi-Source Fusion for Plant Phenotyping
In the context of the booming development of precision agriculture and plant phenotyping, plant 3D reconstruction technology has become a research hotspot, with widespread applications in plant growth monitoring, pest and disease detection, and smart agricultural equipment. Given the complex geometr...
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MDPI AG
2025-05-01
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| Online Access: | https://www.mdpi.com/1424-8220/25/11/3401 |
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| author | Songhang Li Zepu Cui Jiahang Yang Bin Wang |
| author_facet | Songhang Li Zepu Cui Jiahang Yang Bin Wang |
| author_sort | Songhang Li |
| collection | DOAJ |
| description | In the context of the booming development of precision agriculture and plant phenotyping, plant 3D reconstruction technology has become a research hotspot, with widespread applications in plant growth monitoring, pest and disease detection, and smart agricultural equipment. Given the complex geometric and textural characteristics of plants, traditional 2D image analysis methods are difficult to meet the modeling requirements, highlighting the growing importance of 3D reconstruction technology. This paper reviews active vision techniques (such as structured light, time-of-flight, and laser scanning methods), passive vision techniques (such as stereo vision and structure from motion), and deep learning-based 3D reconstruction methods (such as NeRF, CNN, and 3DGS). These technologies enhance crop analysis accuracy from multiple perspectives, provide strong support for agricultural production, and significantly promote the development of the field of plant research. |
| format | Article |
| id | doaj-art-2b03efdc700e403da8d29f7eecd996bb |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-2b03efdc700e403da8d29f7eecd996bb2025-08-20T03:46:46ZengMDPI AGSensors1424-82202025-05-012511340110.3390/s25113401A Review of Optical-Based Three-Dimensional Reconstruction and Multi-Source Fusion for Plant PhenotypingSonghang Li0Zepu Cui1Jiahang Yang2Bin Wang3College of Information Science and Engineering, Shanxi Agricultural University, Jinzhong 030800, ChinaCollege of Information Science and Engineering, Shanxi Agricultural University, Jinzhong 030800, ChinaCollege of Information Science and Engineering, Shanxi Agricultural University, Jinzhong 030800, ChinaCollege of Information Science and Engineering, Shanxi Agricultural University, Jinzhong 030800, ChinaIn the context of the booming development of precision agriculture and plant phenotyping, plant 3D reconstruction technology has become a research hotspot, with widespread applications in plant growth monitoring, pest and disease detection, and smart agricultural equipment. Given the complex geometric and textural characteristics of plants, traditional 2D image analysis methods are difficult to meet the modeling requirements, highlighting the growing importance of 3D reconstruction technology. This paper reviews active vision techniques (such as structured light, time-of-flight, and laser scanning methods), passive vision techniques (such as stereo vision and structure from motion), and deep learning-based 3D reconstruction methods (such as NeRF, CNN, and 3DGS). These technologies enhance crop analysis accuracy from multiple perspectives, provide strong support for agricultural production, and significantly promote the development of the field of plant research.https://www.mdpi.com/1424-8220/25/11/3401plant 3D reconstructionactive vision techniquespassive vision techniquesprecision agriculturepoint cloud data |
| spellingShingle | Songhang Li Zepu Cui Jiahang Yang Bin Wang A Review of Optical-Based Three-Dimensional Reconstruction and Multi-Source Fusion for Plant Phenotyping Sensors plant 3D reconstruction active vision techniques passive vision techniques precision agriculture point cloud data |
| title | A Review of Optical-Based Three-Dimensional Reconstruction and Multi-Source Fusion for Plant Phenotyping |
| title_full | A Review of Optical-Based Three-Dimensional Reconstruction and Multi-Source Fusion for Plant Phenotyping |
| title_fullStr | A Review of Optical-Based Three-Dimensional Reconstruction and Multi-Source Fusion for Plant Phenotyping |
| title_full_unstemmed | A Review of Optical-Based Three-Dimensional Reconstruction and Multi-Source Fusion for Plant Phenotyping |
| title_short | A Review of Optical-Based Three-Dimensional Reconstruction and Multi-Source Fusion for Plant Phenotyping |
| title_sort | review of optical based three dimensional reconstruction and multi source fusion for plant phenotyping |
| topic | plant 3D reconstruction active vision techniques passive vision techniques precision agriculture point cloud data |
| url | https://www.mdpi.com/1424-8220/25/11/3401 |
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