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Feasibility study for the implementation of an automatic system for the detection of social interactions in the waiting area of automatic milking stations by using a video surveillance system

机译:利用视频监控系统实现自动挤奶站候车区社交互动检测自动系统的可行性研究

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A well-planned waiting area is crucial for automatic milking systems. In an enclosed waiting area, cows of different rank compete for entering the milking station and they are exposed for a variety of social interactions. Such interactions could increase standing time and delay milking, which may result in stress, lameness, impaired welfare and reduced performance. The aim was to monitor the waiting area in a free stall dairy by the use of three video cameras to detect occurrence of social interactions by using improved image segmentation and tracking methods. The surveillance system observed 252 cows having free access to any of four milking stations during 24 h over a period of two weeks. A two-step pattern recognition approach was used. In the first step geometric features (distances) were extracted from every pair of cows in every frame. These features form the input of the second step. It consists of a classifier of the behaviour of the cows. A support vector machine was used to realise this classifier. The social interactions were identified based on collision of geometrical shapes segmented from the image and positively identified as cows by experienced observers. The results showed that the proposed system was capable of a fairly accurate detection of social interactions. (C) 2016 Elsevier B.V. All rights reserved.
机译:精心计划的等候区对于自动挤奶系统至关重要。在封闭的等候区,不同等级的母牛争夺进入挤奶站的机会,他们被暴露于各种社交活动中。这种相互作用可能会增加站立时间并延迟挤奶,这可能导致压力,la足,福利受损和性能下降。目的是通过使用三个摄像头来监视免费摊位乳制品中的等候区,以通过使用改进的图像分割和跟踪方法来检测社交互动的发生。监控系统观察到252头母牛在两周内的24小时内可以自由进入四个挤奶站中的任何一个。使用了两步模式识别方法。第一步,从每一帧的每一对母牛中提取几何特征(距离)。这些功能构成了第二步的输入。它由母牛行为的分类器组成。支持向量机用于实现该分类器。基于从图像中分割出的几何形状的碰撞来识别社交互动,并由经验丰富的观察者将其正确识别为母牛。结果表明,所提出的系统能够相当准确地检测社交互动。 (C)2016 Elsevier B.V.保留所有权利。

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