Car Camera Network Could Produce Virtual Maps of Pedestrian 基于车载相机网络的行人虚拟地图

A growing fleet of smart cars may add their street camera views to those of the surveillance camera networks already covering many major cities. That could open the door for a new technology that enables different video cameras to “talk” with one another and track the same individual person across many different camera views.

蓬勃发展的智能汽车也许已经可以将它们自身的车载相机与城市中常见的监控相机连接,这一技术将使得不同的相机之间可以互通信息,并在不同的相机视角下跟踪同一个行人。

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The technology is based on a computer algorithm that can compare different camera views of the same person and learn to recognize the same individuals across many camera views by focusing on body color, texture and movement. Researchers envision a large-scale version of the system tracking pedestrian traffic on a virtual map—perhaps displayed on a car’s GPS screen—or enabling police to easily track fleeing suspects across multiple surveillance camera views.

通过计算机视觉算法对同一行人在不同视角下的比对和学习,以基于颜色、纹理和运动特征实现对同一目标的识别跟踪。研究人员对该技术在大范围内构建行人检测跟踪的虚拟地图充满憧憬-可以在车载导航仪屏幕上显示-或者便于警察在不同的监控摄像头中跟踪同一个嫌疑犯。

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Rresearchers tested the algorithm with cameras placed on moving cars. They trained individual cameras learn to work together in pairs by training them on a certain set of test footage. Such testing led to the new work, which was presented at the Intelligent Transportation Systems Conference sponsored by IEEE and held in Qingdao, China. But the technology does not have to work with only car-mounted cameras. The team has experimented with using their algorithm on cameras carried byflying drones.

研究人员在车载相机上测试了该算法,按照一定的测试进度实现了独立相机之间的协同工作,并在今年在中国青岛举行的智能交通系统会议上做了展示。该技术并非只能在车载相机上实现,该团队已经在无人机上做了同样的测试。

This work is done by the researchers from University of Washington. For further details, please check the available publication on ITSC 2014 and their website.

该工作由华盛顿大学的研究人员完成,更多技术细节请查阅ITSC2014论文和相关研究主页。

Part of the content is from IEEE Spetrum.

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无人驾驶汽车研究员 半吊子摇滚混子乐手 Researcher on Intelligent Vehicle Guitarist/Singer/Rocker
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