Distributed video surveillance using hardware-friendly sparse large margin classifiers
Distributed video surveillance using hardware-friendly sparse large margin classifiers
复制标题
使用硬件友好的稀疏大边缘分类器的分布式视频监控
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
L. Benini
中科院分区：
文献类型：
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作者：
A. Kerhet;F. Leonardi;A. Boni;P. Lombardo;Michele Magno;L. Benini
与仅仅“观察”世界的视频传感器不同，目前的研究旨在开发能够在本地解读世界的智能设备。市场上有很多这样的设备，一方面非常强大，但需要连接电网，或者另一方面需要大量的可充电电池。本文提出的无线视频传感器节点MicrelEye针对不同的设计点：便携性和低功耗预算，同时仍然提供突出的智能水平，即对象分类。为了处理这样一个具有挑战性的任务，我们提出并实现了一种新的类似svm的面向硬件的算法，称为ERSVM。在这项工作中考虑的案例研究是人的检测。所得结果表明，本技术允许设计能够执行局部分类任务的简单智能视频节点。
In contrast to video sensors which just "watch " the world, present-day research is aimed at developing intelligent devices able to interpret it locally. A number of such devices are available on the market, very powerful on the one hand, but requiring either connection to the power grid, or massive rechargeable batteries on the other. MicrelEye, the wireless video sensor node presented in this paper, targets a different design point: portability and a scanty power budget, while still providing a prominent level of intelligence, namely objects classification. To deal with such a challenging task, we propose and implement a new SVM-like hardware-oriented algorithm called ERSVM. The case study considered in this work is people detection. The obtained results suggest that the present technology allows for the design of simple intelligent video nodes capable of performing local classification tasks.