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An automatic system for the detection of dairy cows lying behaviour in free-stall barns

机译:一种用于检测速冻牛舍中奶牛躺卧行为的自动系统

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In this paper, a method for the automatic detection of dairy cow lying behaviour in free-stall barns is proposed. A computer visionbased system (CVBS) composed of a video-recording system and a cow lying behaviour detector based on the Viola Jones algorithm was developed. The CVBS performance was tested in a head-to-head free stall barn. Two classifiers were implemented in the software component of the CVBS to obtain the cow lying behaviour detector. The CVBS was validated by comparing its detection results with those generated from visual recognition. This comparison allowed the following accuracy indices to be calculated: the branching factor (BF), the miss factor (MF), the sensitivity, and the quality percentage (QP). The MF value of approximately 0.09 showed that the CVBS missed one cow every 11 well detected cows. Conversely, the BF value of approximately 0.08 indicated that one false positive was detected every 13 well detected cows. The high value of approximately 0.92 obtained for the sensitivity index and that obtained for QP of about 0.85 revealed the ability of the proposed system to detect cows lying in the stalls.
机译:本文提出了一种自动检测速冻牛舍中奶牛躺卧行为的方法。基于Viola Jones算法,开发了由录像系统和卧牛行为检测器组成的基于计算机视觉的系统(CVBS)。 CVBS性能在无人驾驶的摊位谷仓中进行了测试。在CVBS的软件组件中实现了两个分类器,以获得奶牛躺卧行为检测器。通过将CVBS的检测结果与通过视觉识别生成的检测结果进行比较来验证CVBS。通过比较,可以计算出以下准确性指标:分支因子(BF),遗漏因子(MF),灵敏度和质量百分比(QP)。 MF值约为0.09,表明CVBS每检测到11头母牛,就会漏掉一头母牛。相反,BF值约为0.08,表示每13头检测良好的母牛检测到一个假阳性。灵敏度指数的高值约为0.92,QP的高值约为0.85,这表明所提出的系统能够检测摊位中的母牛。

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