Pezzuolo Andrea, Guarino Marcella, Sartori Luigi, Marinello Francesco
Department of Agroforesty and Landscape, University of Padua, 35020 Legnaro, Italy.
Department of Environmental Science and Policy, University of Milan, 20123 Milan, Italy.
Sensors (Basel). 2018 Feb 24;18(2):673. doi: 10.3390/s18020673.
Frequent checks on livestock's body growth can help reducing problems related to cow infertility or other welfare implications, and recognizing health's anomalies. In the last ten years, optical methods have been proposed to extract information on various parameters while avoiding direct contact with animals' body, generally causes stress. This research aims to evaluate a new monitoring system, which is suitable to frequently check calves and cow's growth through a three-dimensional analysis of their bodies' portions. The innovative system is based on multiple acquisitions from a low cost Structured Light Depth-Camera (Microsoft Kinect™ v1). The metrological performance of the instrument is proved through an uncertainty analysis and a proper calibration procedure. The paper reports application of the depth camera for extraction of different body parameters. Expanded uncertainty ranging between 3 and 15 mm is reported in the case of ten repeated measurements. Coefficients of determination R² > 0.84 and deviations lower than 6% from manual measurements where in general detected in the case of head size, hips distance, withers to tail length, chest girth, hips, and withers height. Conversely, lower performances where recognized in the case of animal depth (R² = 0.74) and back slope (R² = 0.12).
频繁检查牲畜的身体生长情况有助于减少与奶牛不孕症或其他福利问题相关的情况，并识别健康异常。在过去十年中，人们提出了光学方法来提取各种参数的信息，同时避免直接接触动物身体，因为这通常会导致压力。本研究旨在评估一种新的监测系统，该系统适合通过对小牛和奶牛身体部位进行三维分析来频繁检查它们的生长情况。该创新系统基于从低成本结构光深度相机（微软Kinect™ v1）进行的多次采集。通过不确定度分析和适当的校准程序证明了该仪器的计量性能。本文报告了深度相机在提取不同身体参数方面的应用。在十次重复测量的情况下，报告的扩展不确定度在3至15毫米之间。在头部尺寸、臀部距离、肩峰到尾巴长度、胸围、臀部和肩峰高度的情况下，通常检测到决定系数R² > 0.84且与手动测量的偏差低于6%。相反，在动物深度（R² = 0.74）和背部坡度（R² = 0.12）的情况下，性能较低。
