华南农业大学学报2025，Vol.46Issue(3)：429-438,10.DOI:10.7671/j.issn.1001-411X.202405030
基于SLAM与神经辐射场的柑橘幼苗三维重建方法
3D reconstruction of citrus seedlings based on SLAM and NeRF
摘要
Abstract
[Objective]Aiming at the problem that it is difficult to obtain the accurate 3D point cloud of citrus seedlings and their 3D phenotypic parameters to characterize the state of seedlings with the existing 3D reconstruction techniques,this paper proposes a method based on the simultaneous localization and mapping(SLAM)and neural radiance fields(NeRF)for 3D reconstruction of citrus seedlings.[Method]One-year old citrus seedlings were taken as the research object.Firstly,a depth sensor was used to capture the RGB map and depth map of the citrus seedling.Secondly,SLAM was employed to obtain the poses of the depth sensor in each frame of the image.Then,NeRF was trained for citrus seedlings,and the multi-view images with attached positional pose were fed into the multilayer erceptron(MLP).Finally,through supervised training with volume rendering,a high-precision 3D realistic point cloud model of citrus seedlings was reconstructed.[Result]The 3D model of citrus seedlings reconstructed by this method was highly realistic in terms of color and texture,with clear contours and distinct layers,and had real-world level accuracy.Based on this model,the 3D phenotypic parameters of citrus seedlings could be effectively extracted with the accuracy of 97.94%for plant height,93.95%for breadth length,94.11%for breadth width and 97.62%for stem thickness.[Conclusion]This study helps to accelerate the selection and nursery process of excellent citrus seedlings and provides a technical support for the sustainable development of the citrus industry.关键词
柑橘幼苗/植物三维表型/三维重建/神经辐射场/SLAM/深度学习Key words
Citrus seedling/Plant 3D phenotype/3D reconstruction/Neural radiance fields(NeRF)/Simultaneous localization and mapping(SLAM)/Deep learning分类
农业科技引用本文复制引用
郭俊,杨达成,莫振杰,兰玉彬,张亚莉..基于SLAM与神经辐射场的柑橘幼苗三维重建方法[J].华南农业大学学报,2025,46(3):429-438,10.基金项目
岭南现代农业实验室项目(NT2021009) （NT2021009）
高等学校学科创新引智计划(D18019) （D18019）
广东省重点领域研发计划(2019B02022101) （2019B02022101）
广东省科技计划(2018A050506073) （2018A050506073）
