Real-Time People Counting across Spatially Adjacent Non-overlapping Camera Views
Real-Time People Counting across Spatially Adjacent Non-overlapping Camera Views
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DOI：
10.1007/978-3-319-14445-0_7
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发表时间：
2015-01
期刊：
影响因子：
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通讯作者：
R. Akai;Naoko Nitta;N. Babaguchi
中科院分区：
文献类型：
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作者：
R. Akai;Naoko Nitta;N. Babaguchi
对穿过非重叠相机视图行进的人的数目进行计数通常需要在离开任何相机视图的所有人重新进入其空间上相邻的相机视图中的一者时重新识别所述人。为了准确地重新识别他们，应该建立所有人的出入之间的对应关系，以便最大化他们的总对应置信度。为了实现实时人数统计，我们提出了寻找最短的时间窗口，以观察所有的人在时间窗口内旅行的出口和入口自适应当前的人流量。此外，由于密切相关的人经常一起旅行，因此可以对前景区域执行重新识别以重新识别人群。由于人群有时会在摄像机视图之外分裂或合并，因此所提出的方法基于其对应置信度在前景区域的出口和入口之间建立加权对应。实验结果表明，自适应确定的时间窗口是有效的准确性和延迟的人计数和加权对应是有效的准确性，特别是当人流量变得拥挤和人群的分裂/合并以外的相机视图。
Counting the number of people traveling across non- overlapping camera views generally requires all persons exiting any camera view to be re-identified when they re-enter one of its spatially adjacent camera views. For their accurate re-identification, the correspondence among the exits and entries of all persons should be established so that their total correspondence confidence is maximized. In order to realize the real-time people counting, we propose to find the shortest time window to observe both the exits and entries of all persons traveling within the time window adaptively to the current people traffic flow. Further, since closely related people often travel together, the re-identification can be performed to the foreground regions to re-identify groups of people. Since the groups of people can sometimes split or merge outside the camera views, the proposed method establishes the weighted correspondence among the exits and entries of the foreground regions based on their correspondence confidence. Experimental results have shown that the adaptively determined time window was effective in terms of both the accuracy and the delay in people counting and the weighted correspondence was effective in terms of the accuracy especially when the people traffic gets congested and groups of people split/merge outside the camera views.