基于分块分割的CAMShift算法用于分布式智能摄像机实时目标跟踪

Manjunath Kulkarni, Paras Wadekar, Haresh Dagale
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引用次数: 3

摘要

本文提出了一种基于直方图的分布式智能摄像机实时目标跟踪系统。每个这样的智能摄像头模块包括一个摄像头和一个嵌入式设备,该设备能够完全自行执行目标跟踪任务。该模块可以实时识别和跟踪目标。然后将包含所标记对象的经过处理的视频流传输到中央服务器以进行显示。在嵌入式设备上运行了本文提出的基于分块的新型CAMShift算法。我们表明,这种技术减少了所需的计算次数,因此更适合嵌入式平台。该解决方案是通过一个中央服务器和多个相机模块实现的,这些模块在室内环境中具有不重叠的视场。通过将实验结果与现有解决方案进行比较,验证了性能的改进。
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Block Division Based CAMShift Algorithm for Real-Time Object Tracking Using Distributed Smart Cameras
In this paper, we present a histogram based real-time object tracking system using distributed smart cameras. Each such smart camera module consists of a camera and an embedded device that is capable of performing the task of object tracking entirely by itself. The module recognizes and tracks the object in real time. The processed video stream containing the marked object is then transmitted to a central server for display. The embedded device runs a novel block division based CAMShift algorithm proposed in this paper. We show that this technique reduces the number of computations required and hence is more suitable for embedded platforms. The solution is implemented using a central server and multiple camera modules with non-overlapping fields of view in indoor settings. We validate the improvement in the performance by comparing the experimental results with existing solutions.
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