Computers and Electronics in Agriculture

• Automated computer vision system for cattle body measurements is designed. • Non-rigid alignment algorithm generates an accurate 3-D model of live cattle. • Open access database with RGB-D and manual measurements for 103 cattle is created. Body condition scoring of livestock is widely used as a subjective method for assessing energy reserves and making management decisions for livestock. Since animal dimensions are often measured manually, the procedure is time-consuming, expensive and stressful for both the farmer and animal. Recent advances in three-dimensional sensor technology provide innovative tools for the design of automated contactless systems for assessing the animal body condition. The objective of this paper is to design an automated computer vision system capable to generate an accurate three-dimensional model of live cattle. The system is based on a non-rigid 3-D shape reconstruction utilizing data from depth cameras. The design methodology includes three Microsoft Kinect v2 cameras, computer vision, signal filtering of point clouds, pattern recognition using 3-D feature extraction techniques, and statistical analysis using point and interval estimations. The quality of generated three-dimensional body models is validated against manually measured nine references, such as withers height, hip height, chest depth, oblique body length, heart girth, etc. With a 90% confidence level, measurement errors in the proposed system among all measured estimates are less than 3%. Experimental results show that the proposed approach can serve as a new accurate method for non-contact body measurement of livestock.

Accurate body measurement of live cattle using three depth cameras and non-rigid 3-D shape recovery