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A comparative study of feature point matching versus foreground detection for computer detection of dairy cows in video frames

机译:视频帧中奶牛的特征点匹配与前景检测的比较研究

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Behaviours of dairy cows reflect their health and emotions. Behavioural analysis by video surveillance is an accepted technique for helping cow-keepers to spot their cows' health problems. To perform a behavioural analysis, the presence and location of the cows need to be detected first. In this study, we used feature point matching method and foreground detection method to detect them. Two experiments were conducted in a dairy farm to detect cows in video frames recorded by a video camera installed over the top of a free-stall barn. A total of 800 frames of recorded cows' activities were captured. True and false positive and negative results were statistically confirmed by t test. We found that the accuracies of the feature point matching and foreground detection methods were 38.55 and 75.95 %, respectively; hence, for our setup, the foreground detection was a better method.
机译:奶牛的行为反映了他们的健康和情绪。通过视频监视进行行为分析是一种可以帮助奶牛饲养者发现奶牛健康问题的公认技术。要进行行为分析,首先需要检测母牛的存在和位置。在这项研究中,我们使用特征点匹配方法和前景检测方法来检测它们。在一个奶牛场进行了两个实验,以检测安装在一个无货仓顶部的视频摄像机记录的视频帧中的母牛。总共记录了800帧奶牛的活动。通过t检验在统计学上确认真假阳性和阴性结果。我们发现特征点匹配和前景检测方法的准确度分别为38.55%和75.95%。因此,对于我们的设置,前景检测是一种更好的方法。

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