Cattle weight estimation from dense point clouds.

CASTANHEIRO, L. F.; TETILA, E. C.; FURUYA, D. E. G.; SILVA, J. P. da; BARBEDO, J. G. A.; ROMANI, L. A. S.; BOLFE, E. L.

Cattle weight estimation from dense point clouds.

Autores

Descripción

Cattle weight is essential for decision-making in precision livestock farming, directly supporting nutrition management, animal welfare, and production efficiency. Existing methods rely on close-range measurements or manual intervention, limiting scalability. This work proposes an workflow for cattle weight estimation based on point clouds derived from aerial images. RGB images acquired at low altitude were processed using Structure from Motion (SfM) techniques to generate dense point clouds. Individual animals were automatically segmented from the reconstructed 3D scene, and voxel-based volumetric features were extracted for each animal. Body weight was then estimated through linear regression models calibrated with ground truth measurements obtained from individual weighing. The proposed approach was evaluated on Nellore cattle in a feedlot environment and achieved a root mean square error (RMSE) of 8.35 kg, corresponding to an average relative error of approximately 2.29%. The results highlight the potential of UAV-based photogrammetry as a cost-effective decision support tool for digital and sustainable livestock management.
Editors: Joaquim Filipe, Michal Smialek, Alexander Brodsky, Slimane Hammoudi. ICEIS 2026.

Palabras clave

Estrutura a partir do movimento, Reconstrução 3D, Pecuária de precisão, Estimativa de peso, Structure-from-Motion, 3D Reconstruction, Precision livestock, Gado de Corte, Unmanned aerial vehicles, Cattle