基于改进FlowNet 2.0光流算法的奶牛反刍行为分析方法  

Ruminant Behavior Analysis Method of Dairy Cows with Improved FlowNet 2.0 Optical Flow Algorithm

作　　者：姬江涛 刘启航 高荣华[2,3] 李奇峰 赵凯旋[1] 白强 JI Jiangtao;LIU Qihang;GAO Ronghua;LI Qifeng;ZHAO Kaixuan;BAI Qiang(College of Agricultural Engineering,Henan University of Science and Technology,Luoyang 471003,China;National Engineering Research Center for Information Technology in Agriculture,Beijing 100097,China;Research Center of Information Technology,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China)

机构地区：[1]河南科技大学农业装备工程学院,洛阳471003 [2]国家农业信息化工程技术研究中心,北京100097 [3]北京市农林科学院信息技术研究中心,北京100097

出　　处：《农业机械学报》2023年第1期235-242,共8页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家重点研发计划项目(2019YFE0125400);国家自然科学基金项目(32002227);北京市农林科学院科技创新能力建设专项(KJCX20220404)。

摘　　要：反刍行为与奶牛生产、繁殖性能及疾病等因素密切相关,针对非接触式奶牛反刍行为分析受牛只自身运动或背景干扰等不足,提出改进FlowNet 2.0光流算法,首先计算垂直光流分量替代光流速度构建光流图,消除水平运动对光流分析干扰;其次设置光流阈值避免垂直光流中头部运动光流干扰;同步计算反刍区域面积阈值提取区域内光流数据,避免目标对象头部运动对反刍光流的影响;最后滤波拟合计算反刍曲线,确定曲线周期,增大波峰波谷差值,提升奶牛反刍咀嚼频次计数的准确性。以不同场景下20头奶牛的30段反刍行为视频为数据集,验证本文方法的有效性、鲁棒性与准确性,试验结果表明,改进FlowNet 2.0光流算法计算奶牛反刍咀嚼频次准确率为99.39%,相较于FlowNet 2.0光流算法准确率提升5.75个百分点。Ruminant behavior is closely related to dairy cow production, reproductive performance, disease and other factors. To overcome the shortage of non-contact dairy cow ruminant behavior analysis caused by cow movement or background interference, the FlowNet 2.0 optical flow algorithm was improved. Firstly, the vertical optical flow component was calculated instead of the optical flow velocity to construct an optical flow diagram to eliminate horizontal movement interference on optical flow analysis. Secondly, the optical flow threshold was set to avoid the interference of head movement flow in vertical optical flow. The area threshold of the ruminant area was calculated and the optical flow data was extracted in the region to avoid the influence of head movement flow of the target object. Finally, filter fitting was used to calculate the rumination curve, determine curve period, increase the difference between peak and valley, and improve the accuracy of counting of rumination frequency in dairy cows. The validity, robustness and accuracy of this method were validated by using 20 dairy cows and 30 ruminant videos in different scenarios. The results showed that the accuracy of improved FlowNet 2.0 optical flow algorithm was 99.39% and 5.75 percentage points higher than that of FlowNet 2.0 optical flow algorithm.

关 键 词：奶牛 FlowNet 2.0 光流 反刍行为 咀嚼频次 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]