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

机译:基于动态图像的多目标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:在图像序列分析的基础上,提出了一种新的乘客上下车自动计数方法。特别是它解决了公交车拥挤和照明变化时的计数问题。通过提取和跟踪出现在图像序列中的乘客的头部及其移动方向,分别计算上下车的乘客人数。多目标识别和跟踪是旅客计数的关键任务。在前景与背景减法分离后,通过对相连的二进制前景图像进行分析来提取真实对象,并提取其特征。然后,针对区域代表的跟踪多目标提出了块匹配算法,并根据匹配结果判断运动方向。实验结果表明,所提出的方法能够正确实现高密度上下车乘客的计数,提高了计数的准确性。

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