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Object detection and modeling algorithm for automatic visual people counting system

机译:自动视觉人数统计系统的目标检测与建模算法

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摘要

This paper presents object detection and modeling algorithm for automatic visual people counting system to identify individuals from top view images acquired from an overhead surveillance camera. This work proposes Snake algorithm with effective external energy function and a half-circle template initialization for modeling passengers. The experiment result showed that the proposed method could fit the Snake to the head and shoulder boundaries of the passengers effectively. Fitting error of 3.76 pixels per control point was obtained in our experiment. The information is not only useful for verifying humans but also for extracting appearance features to enhance performance of the subsequent tracking algorithm.
机译:本文提出了一种用于自动视觉人数统计系统的对象检测和建模算法,该算法可从从高架监视摄像机获取的顶视图图像中识别出个人。这项工作提出了具有有效外部能量功能和半圆形模板初始化的Snake算法,用于对乘客进行建模。实验结果表明,所提出的方法可以有效地使蛇与乘客的头肩边界相吻合。在我们的实验中,每个控制点的拟合误差为3.76像素。该信息不仅对验证人员有用,而且对于提取外观特征以增强后续跟踪算法的性能也很有用。

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