arXiv Computer Vision By Therin Young, Elijah Rodriguez, Lisa Coffey, Talukder Zaki Jubery, Adarsh Krishnamurthy, Patrick Schnable, Baskar Ganapathysubramanian

AI-enabled Low-Cost 3D Maize Ear Morphometry Platform at Breeding Scale

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arXiv Computer Vision
Sep 3

Automated Maize Ear Phenotyping Using 3D Reconstructions

The paper presents a fully automated pipeline that extracts maize ear traits—such as kernel count, row number, and kernel size—from 3D point clouds generated by a video-to-point-cloud platform. The method processes raw video through COLMAP and NeRF, isolates the ear, calibrates the point cloud, aligns it, unwraps it into a 2D image, and applies Cellpose‑SAM for instance segmentation, achieving high accuracy (kernel count R² = 0.921, MAPE = 10.33 %) on a held‑out dataset. The resulting multi‑trait dataset, with genotype identities, is ready for phenotype‑to‑genotype association studies.

By Ritwesh A. Kumar, Som Tripathi, Peja Matthews, Srikar Reddy, Talukder Zaki Jubery, Patrick Schnable, Adarsh Krishnamurthy, Baskar Ganapathysubramanian
arXiv Machine Learning
Aug 10

UAV3DCrop: Benchmarking 3D Reconstruction in Repeated Multi-Angle UAV Crop Surveys

arXiv:2608. 06404v1 Announce Type: cross Abstract: Accurate 3D crop monitoring underpins data-driven precision agriculture by enabling field-scale analysis of plant structure, growth dynamics, and management response.

By Junxiong Zhou, Xuechen Li, Chonghao Qiu, Lang Qiao, Xiaowei Jia, Qi Yang, Chishan Zhang, Leikun Yin, Nanshan You, Vipin Kumar, David Mulla, Ce Yang, Zhenong Jin, Licheng Liu
Hugging Face Trending Papers
Jul 2

The Turning Point of 3D Plant Phenotyping: 3D Foundation Models Enable Minute-to-Second Cross-Crop Reconstruction and Beyond

3D plant phenotyping is notoriously known to be procedure-complicated and of low throughput due to the extensive multi-view imaging, the fragile 3D reconstruction pipeline, and the additional cost from reconstructed geometry to phenotypic extraction. These limitations are further amplified in low-cost data acquisition, where smartphone videos or sparsely sampled multi-view images provide limited view overlap and self-occlusion.