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People counting system based on improved Gaussian background model

机译：基于改进高斯背景模型的人数统计系统

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This paper introduces a novel method to count people which is applied to the ATM surveillance video. In this system, we chose an image without foreground target as the background image. To reduce the interference, updating the background in real-time is a must, and the foreground image is got by the improved Gaussian background difference between current image and background image, then binarizing and morphology processing. After dilating and eroding, the contours of people are clearly presented. We take the contour as a person if the number of the pixels in the contour is more than a certain threshold, and the number of the contours is the number of people. In the end, we utilize the ratio of width to height of the contours to improve the accuracy.
机译：本文介绍了一种应用于ATM监控视频的人数统计新方法。在该系统中，我们选择了没有前景目标的图像作为背景图像。为了减少干扰，必须实时更新背景，并且通过改进当前图像与背景图像之间的高斯背景差异，然后对图像进行二值化和形态学处理，得到前景图像。经过扩张和腐蚀后，人们的轮廓清晰可见。如果轮廓中的像素数大于某个阈值，则以轮廓为人，轮廓数为人的数量。最后，我们利用轮廓的宽高比来提高精度。

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