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Automatic passenger counting based on multi-objects recognition using dynamic images

机译:基于使用动态图像的多对象识别的自动乘客计数

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Based on image sequences analysis, a new automatic counting method of passengers getting on and off a bus is proposed. In particular, it addresses the problem of counting when bus is crowded and illumination changes. By extracting and tracking passengers' heads appearing in image sequences and their moving direction, passengers boarding and alighting a bus are counted respectively. The multi-objects recognition and tracking is the key task of passenger counting. After foreground is separated from background subtraction, true objects are extracted through analysis on connected binary foreground image and their features are also extracted. Then, block matching algorithm is presented for the tracking multi-objects represented by regions and moving direction is judged according the result of matching. The experiment results show that the proposed method can realize counting passenger getting on and off a bus in high density correctly and improve the accuracy of counting.
机译:基于图像序列分析,提出了一种新的乘客自动计数方法,乘坐乘客上乘坐公共汽车。特别是,它解决了乘坐公共汽车拥挤和照明变化时计算的问题。通过提取和跟踪乘客的头部出现在图像序列中,分别计算乘客登机和乘坐公共汽车。多对象识别和跟踪是乘客计数的关键任务。前景与背景减法分离后,通过对连接的二进制前景图像分析提取真实对象,并且还提取它们的功能。然后,为由区域表示的跟踪多物体呈现块匹配算法,并且根据匹配结果判断移动方向。实验结果表明,该方法可以正确实现计数乘客高密度的乘坐,并提高计数的准确性。

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