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Automatic real-time monitoring of locomotion and posture behaviour of pregnant cows prior to calving using online image analysis

机译:使用在线图像分析,在产犊前自动实时监测怀孕母牛的运动和姿势行为

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摘要

Monitoring the locomotion and posture behaviour of pregnant cows close to calving is essential in determining if there is a need for human intervention to assist parturition. In this study an automatic real-time monitoring technique is described in detail which allows identifying the locomotion and posturing behaviour of pregnant cows prior to calving. For this purpose video surveillance images of eight cows for the last 24h prior to their calving were analysed. Data on seven different variables with time were obtained for each cow using an automatic real-time monitor. These were namely: x-y coordinates of the geometrical top view centre point of the cow; walking trajectory; distance walked; orientation of the main axis; body width/length ratio; hip length and back area. These variables were then used to classify specific behaviours such as standing or lying (including incidences of motion during lying), and eating or drinking. On average 85% of the standing and lying and 87% of the eating or drinking behaviour of the eight cows during the last 24h before calving could be correctly classified. However, the developed technique needs to be further validated with additional tests in the field.
机译:在确定是否需要人工干预来辅助分娩时,监测接近产犊的母牛的运动和姿势行为至关重要。在这项研究中,详细描述了一种自动实时监视技术,该技术可以在产犊前识别怀孕母牛的运动和姿势行为。为此,分析了八头母牛产犊前最后24小时的视频监控图像。使用自动实时监控器,为每头母牛获得了七个随时间变化的变量的数据。它们是:母牛的几何顶视图中心点的x-y坐标;行走轨迹步行距离;主轴方向;体长/体长比;臀部长度和背部。然后将这些变量用于对特定行为进行分类,例如站立或躺着(包括躺着时发生运动的发生率)以及进食或饮水。在产犊前的最后24小时内,这八头母牛的平均站立和躺卧状态的85%和进食或饮水行为的87%可以正确分类。但是,开发的技术需要通过现场其他测试进一步验证。

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