Monocular Mesh Recovery and Body Measurement of Female Saanen Goats

2026-02-23

AI Summary

This study addresses the lack of high-precision 3D body conformation data for female Saanen dairy goats, which hinders accurate assessment of their milk production potential. To this end, we present the first breed-specific parametric 3D body model for Saanen goats, integrating multi-view RGB-D data with DynamicFusion-based dynamic point cloud reconstruction. The model incorporates 41 skeletal keypoints and a refined mammary representation, enabling personalized morphological modeling. Using only a single-view RGB-D input, our system achieves high-fidelity 3D reconstruction and automatically extracts six key linear body measurements—body length, withers height, chest width, heart girth, rump width, and rump height—with high accuracy. Experimental results demonstrate that our approach significantly outperforms existing methods in both reconstruction fidelity and body conformation evaluation performance.

Technology Category

• Computer Vision: 3D Computer Vision
• Machine Learning: Learning with Manifolds
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

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.

Problem

• monocular mesh recovery
• body measurement
• Saanen goats
• 3D reconstruction
• precision livestock farming

Innovation

• parametric 3D shape model
• monocular 3D reconstruction
• precision livestock farming
• DynamicFusion
• body measurement automation