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首页> 外文期刊>Indian Journal of Science and Technology >Field Seeding Algorithm for People Counting Using KINECT Depth Image
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Field Seeding Algorithm for People Counting Using KINECT Depth Image

机译:使用KINECT深度图像进行人口计数的场播算法

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In this work, we present a people counting algorithm using depth images acquired from a KINECT camera that is installed vertically, i.e., pointing toward the floor. Our proposed algorithm is referred to as Field seeding algorithm. The key idea is that first a set of local minimum values are detected from several spatially distributed seed locations. Then, the peoplehead blobs are detected from the binary images generated with regard to the threshold values derived from the local minimum values. The recall, accuracy and F-score of our algorithm are comparable to the current state-of-the-art people counting using KINECT, i.e. Water Filling. However, the main advantage over the previous method is that our algorithm operates deterministically, i.e., no any random number generating function is used.
机译:在这项工作中,我们提出一种人员计数算法,该算法使用从垂直安装(即指向地板)的KINECT摄像机获取的深度图像进行计数。我们提出的算法称为场播种算法。关键思想是,首先从几个空间分布的种子位置中检测出一组局部最小值。然后,从关于从局部最小值导出的阈值生成的二进制图像中检测出人头斑点。我们算法的召回率,准确性和F分数与使用KINECT进行计数的当前最先进的人员相当,即注水。但是,与以前的方法相比,主要优点是我们的算法可确定性地运行,即不使用任何随机数生成函数。

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