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Prioritized target tracking with active collaborative cameras

机译:优先使用主动协作摄像机的目标跟踪

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Mobile cameras on robotic platforms can support fixed multi-camera installations to improve coverage and target localization accuracy. We propose a novel collaborative framework for prioritized target tracking that complement static cameras with mobile cameras, which track targets on demand. Upon receiving a request from static cameras, a mobile camera selects (or switches to) a target to track using a local selection criterion that accounts for target priority, view quality and energy consumption. Mobile cameras use a receding horizon scheme to minimize tracking uncertainty as well as energy consumption when planning their path. We validate the proposed framework in simulated realistic scenarios and show that it improves tracking accuracy and target observation time with reduced energy consumption compared to a framework with only static cameras and compared to a state-of-the-art motion strategy.
机译:机器人平台上的移动摄像机可以支持固定的多摄像机安装,以提高覆盖率和目标本地化精度。我们提出了一种新颖的协作框架,用于优先考虑与移动摄像机的静态摄像机补充静态相机,这是按需跟踪目标。在从静态摄像机接收到请求时,移动摄像机选择(或切换到)目标以使用占目标优先级的本地选择标准来跟踪,从而查看质量和能量消耗。移动摄像机使用后退地平线方案来最小化跟踪不确定性以及规划路径时的能量消耗。我们验证了模拟现实情景中提出的框架,并表明它可以提高与仅具有静态相机的框架相比降低能量消耗的跟踪精度和目标观察时间,并与最先进的运动策略相比。

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