面向视觉传感器网络广域目标鲁棒跟踪的个体轮廓提取

Xiaoling Wu, Hoon Heo, R. Shaikh, Jinsung Cho, O. Chae, Sungyoung Lee
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引用次数: 10

摘要

在本文中,我们提出了一种利用配备摄像机的视觉传感器网络协同跟踪广域运动目标的方法,该方法有望在监视和监控等各种应用中发挥重要作用。采用高效轮廓提取的遗传拟合方法作为场景间检测和跟踪目标的方法。考虑到网络中存在故障传感器会降低目标跟踪问题的难度,提出了一种鲁棒传感器协同方法。实验结果表明,与现有的目标跟踪方法相比,所提出的目标跟踪方法能够很好地跟踪目标,特别是当目标与背景中的相邻目标相邻时
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Individual contour extraction for robust wide area target tracking in visual sensor networks
In this paper, we propose an approach to collaboratively track motion of a moving target in a wide area utilizing camera-equipped visual sensor networks, which are expected to play an essential role in a variety of applications such as surveillance and monitoring. A genetic fitting method for efficient contour extraction is used as inter-scene approach to detect and track the target. We also considered the existence of faulty sensors in the network which deteriorate the difficulty of target tracking problem, and proposed a robust sensor collaboration method. The experimental results have shown that the proposed target tracking approach produces very successful target tracking compared with the existing method especially in case that the target is adjacent to neighboring objects of background
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