分布式智能摄像机网络中在线视觉图生成与切换的社会经济方法

Lukas Esterle, Peter R. Lewis, Marcin Bogdański, B. Rinner, X. Yao
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引用次数: 38

摘要

在本文中,我们提出了一种基于自利自主相机的方法,该方法在市场机制中交换跟踪对象的责任,以最大化其自身的效用。一种新颖的受蚁群启发的机制被用于在运行时生长视觉图,然后可以用来优化相机之间的通信。我们完全分散的方法的主要好处是一方面在线生成视觉图,允许在运行期间向网络添加和删除摄像机,另一方面仅依赖于本地信息,增加了系统的鲁棒性。由于我们基于市场的方法不依赖于先验的拓扑信息,因此可以避免任何多摄像机校准的需要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A socio-economic approach to online vision graph generation and handover in distributed smart camera networks
In this paper we propose an approach based on self-interested autonomous cameras, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to grow the vision graph during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online which permits the addition and removal cameras to the network during runtime and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multi-camera calibration can be avoided.
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