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A Study on the Implementation of Networked Image-Sensing by Using Smart Image Sensors

机译:利用智能图像传感器实现网络图像传感的研究

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摘要

Large-scale image sensing over the extended area and time is very effective to obtain global information, which can be attained by the local information from the spatially-distributed sensors for long-term period. However, on the other hand, how to overcome the bandwidth problem caused by huge data volume is one of the crucial issues to implement a practical system. From the viewpoint of communication bandwidth, we consider that it would be very cost-effective if the necessary data only can be acquired and transmitted at necessary time. In this paper, an experimental system using a group of Spatially-Variant Sampling (SVS) smart image sensors is presented. This system is targeted to reduce the data volume at image acquisition level by utilizing selective spatial/temporal resolution reduction schemes, taking into considerations of the priority of particular regions of the scenes. The main advantage of this system is the pixel-level handling of images on sensor nodes and a host, which contributes to the better efficiency and more flexibility in data management, because this system has no need for encoding/decoding of the image data, which is normally very computationally-intensive when the large number of image sensors are involved.
机译:在扩展的区域和时间上进行大规模图像感测对于获得全局信息非常有效,这可以通过长期分布在空间分布传感器中的本地信息来获得。然而,另一方面,如何克服由庞大的数据量引起的带宽问题是实现实用系统的关键问题之一。从通信带宽的角度来看,我们认为如果仅在必要的时间获取和发送必要的数据,则将非常具有成本效益。在本文中,提出了使用一组空间变量采样(SVS)智能图像传感器的实验系统。该系统旨在通过考虑场景特定区域的优先级,通过使用选择性的空间/时间分辨率降低方案来减少图像采集级别的数据量。该系统的主要优点是传感器节点和主机上图像的像素级处理,这有助于提高数据管理的效率和灵活性,因为该系统无需对图像数据进行编码/解码。当涉及大量图像传感器时,通常是非常耗费计算资源的。

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