计算机科学
高斯分布
人工智能
计算机图形学(图像)
物理
量子力学
作者
T.P. Ojo,Thai La,A. Morton,Ian Stavness
标识
DOI:10.1145/3681758.3698009
摘要
3D capture and characterization of plant shoot architecture is a grand challenge in plant phenotyping research, made difficult by plants' intricate 3D shape, composed of thin and flat sub-structures (stems, leaves, flowers, pods, etc.). In this paper, we show that 3D gaussian splatting is well-suited for capturing 3D plant representations, which we call splants. We report a simple and fast capture procedure and 3DGS processing software that is tailored to foreground object capture. Splant generation worked well across plant species and growth stages. Our preliminary results point to a promising future for splant phenotyping, which we expect will lead to a dramatic increase in the use of multi-view imaging and 3D analysis in plant pathology and plant breeding research.
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