中国畜牧兽医2026，Vol.53Issue(5)：2276-2289,14.DOI:10.16431/j.cnki.1671-7236.2026.05.009
基于三维点云与几何先验补偿的牛体体尺测定
Body Measurement of Cattle Based on 3D Point Cloud and Geometric Prior Compensation
摘要
Abstract
[Objective]To address the problems of low efficiency in manual body measurement and the lack of standardized measurement data in the large-scale breeding of dual-purpose cattle,this study aimed to construct a high-throughput measurement system based on 3D point clouds.[Method]Taking 203 adult Simmental cattle in Xinjiang as subjects,a"top-view+side-view"multi-angle camera array integrating five cameras was deployed.A hardware synchronization network was constructed to eliminate motion artifacts caused by the cattle's natural walking.The algorithmic pipeline included multi-camera registration based on the iterative closest point(ICP)algorithm and voxel grid denoising.Furthermore,addressing the visual blind spots and point cloud loss in the hind leg region during natural walking,a dynamic occlusion compensation algorithm based on geometric priors was innovatively proposed.Using manual measurement as the standard,system performance was evaluated using Bland-Altman plots and linear regression models.[Result]A natural walking speed of 1.5 m/s,the frame acquisition time was approximately 0.06 s,and the core algorithm calculation took 1.79 s,improving comprehensive efficiency by about 60 times compared with manual methods.The system demonstrated high robustness for rigid traits such as height at withers and hip height,achieving measurement accuracies of 95.94%and 96.60%,respectively,with error distributions exhibiting good unimodal symmetry.For the challenging hind leg semi-girth,the compensation strategy based on geometric priors effectively overcame camera blind spots under dynamic conditions,achieving an accuracy of 89.05%with significant data consistency and no proportional bias.[Conclusion]This study constructed a non-contact body measurement system for cattle based on multi-view 3D point clouds,achieving automated collection at 1.85 s.The research confirmed that the system's measurement accuracy for height at withers,hip height,and other rigid traits exceeded 95%.Addressing the hind leg occlusion issue,the proposed geometric compensation algorithm effectively filled visual blind spots.This technology effectively resolved the difficulties of phenotype data collection in complex dynamic environments,providing standardized data support for the genetic breeding of cattle and the development of precision livestock farming.关键词
西门塔尔牛/三维点云/精准畜牧业/高通量表型/体尺测定Key words
Simmental cattle/3D point cloud/precision livestock farming/high-throughput phenotyping/body measurement分类
农业科技引用本文复制引用
李乐天,马为红,陈秋明,李奇峰,李明宇,薛向龙,郭宇航,于沁杨,徐源,黄锡霞..基于三维点云与几何先验补偿的牛体体尺测定[J].中国畜牧兽医,2026,53(5):2276-2289,14.基金项目
创新研究院-农业人工智能与机器人:肉牛数字化育种系统研发——肉牛体尺体重表型高通量无应激测量系统 （）
国家重点研发计划项目(2021YFD1200900) （2021YFD1200900）
北京市智慧农业创新团队项目资助(BAIC10-2026) （BAIC10-2026）
