Abstract
<p>The timely acquisition of agricultural information is fundamental to smart agriculture, providing a basis for decision-making in agricultural production and ensuring protection against risks. With advancements in computer vision and machine learning, 3D reconstruction, the process of generating detailed digital models, has demonstrated substantial potential for mining and recording crucial information from objects, including geometry, structural attributes, visual appearance and other properties. This paper summarizes the applications of 3D reconstruction and measurement in the field of agricultural information acquisition based on prior research. It first reviews the 3D reconstruction and its related techniques and algorithms, then conducts a comprehensive analysis of the applications of 3D reconstruction and measurement in crop cultivation, animal husbandry, aquaculture and post-harvest products. It can be concluded that compared to traditional two-dimensional imagery, 3D reconstruction and measurement offer richer and more comprehensive information for agricultural practices, showing better performance in tasks such as organ segmentation, geometry measurement, health monitoring and simulation analysis. Future works can be launched from keeping up with the latest reconstruction technology, accelerating the 3D reconstruction, fusing multi-sensor data and combining 3D reconstruction with other information acquisition technologies.</p>
Published Version
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