The lactation performance of Saanen dairy goats, renowned for their high milk yield, is intrinsically linked to their body size, making accurate 3D body measurement essential for assessing milk production potential, yet existing reconstruction methods lack goat-specific authentic 3D data. To address this limitation, we establish the FemaleSaanenGoat dataset containing synchronized eight-view RGBD videos of 55 female Saanen goats (6-18 months). Using multi-view DynamicFusion, we fuse noisy, non-rigid point cloud sequences into high-fidelity 3D scans, overcoming challenges from irregular surfaces and rapid movement. Based on these scans, we develop SaanenGoat, a parametric 3D shape model specifically designed for female Saanen goats. This model features a refined template with 41 skeletal joints and enhanced udder representation, registered with our scan data. A comprehensive shape space constructed from 48 goats enables precise representation of diverse individual variations. With the help of SaanenGoat model, we get high-precision 3D reconstruction from single-view RGBD input, and achieve automated measurement of six critical body dimensions: body length, height, chest width, chest girth, hip width, and hip height. Experimental results demonstrate the superior accuracy of our method in both 3D reconstruction and body measurement, presenting a novel paradigm for large-scale 3D vision applications in precision livestock farming.

翻译：以高泌乳量著称的萨能奶山羊的泌乳性能与其体型尺寸密切相关，因此精确的三维体型测量对于评估产奶潜力至关重要，然而现有重建方法缺乏山羊专用的真实三维数据。为突破这一局限，我们构建了FemaleSaanenGoat数据集，包含55只雌性萨能山羊（6-18月龄）的同步八视角RGBD视频序列。通过多视角DynamicFusion技术，我们将含噪声的非刚性点云序列融合为高保真三维扫描模型，克服了山羊体表不规则形变与快速运动带来的重建挑战。基于这些扫描数据，我们开发了专为雌性萨能山羊设计的参数化三维形状模型SaanenGoat。该模型采用包含41个骨骼关节的精细化模板并强化了乳房区域表征，且与我们的扫描数据完成了配准。通过48只山羊样本构建的完整形状空间，能够精确表征个体间的形态差异。借助SaanenGoat模型，我们实现了从单视角RGBD输入的高精度三维重建，并自动化测量了六项关键体型尺寸：体长、体高、胸宽、胸围、臀宽与臀高。实验结果表明，我们的方法在三维重建与体型测量方面均具有优越的准确性，为精准畜牧业中的大规模三维视觉应用提供了创新范式。