自定位智能摄像头网络

Babak Shirmohammadi, C. J. Taylor
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引用次数: 22

摘要

本文描述了一种定位嵌入式摄像机和传感器网络的新方法。在这个方案中,摄像头和传感器配备了可控光源(可见光或红外线),用于信号发送。然后,每个相机节点可以自动确定从其有利位置可见的所有节点的方位。通过将这些测量结果与机载加速度计获得的测量结果融合,相机节点能够确定网络中其他节点的相对位置和方向。该方法使用从图像中获得的角度测量,而不是从飞行时间或信号衰减中获得的距离测量。该方案可以相对容易地使用常见的组件来实现,并且由于定位计算利用了测量系统的稀疏结构,因此它具有良好的可扩展性。此外,该方法提供了相机方向的估计,这不能仅仅从距离测量来确定。本地化技术可以作为构建高级应用程序的基本功能。该方法还可用于自动测量感兴趣传感器的位置,实施分布式监视系统,或基于从多个注册有利位置获得的图像分析场景结构。它还提供了一种机制,用于将从摄像机获得的图像与从分布式传感器获得的测量值集成在一起。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-localizing smart camera networks
This article describes a novel approach to localizing networks of embedded cameras and sensors. In this scheme, the cameras and the sensors are equipped with controllable light sources (either visible or infrared), which are used for signaling. Each camera node can then determine automatically the bearing to all of the nodes that are visible from its vantage point. By fusing these measurements with the measurements obtained from onboard accelerometers, the camera nodes are able to determine the relative positions and orientations of other nodes in the network. The method uses angular measurements derived from images, rather than range measurements derived from time-of-flight or signal attenuation. The scheme can be implemented relatively easily with commonly available components, and it scales well since the localization calculations exploit the sparse structure of the system of measurements. Additionally, the method provides estimates of camera orientation which cannot be determined solely from range measurements. The localization technology could serve as a basic capability on which higher-level applications could be built. The method could also be used to automatically survey the locations of sensors of interest, to implement distributed surveillance systems, or to analyze the structure of a scene, based on images obtained from multiple registered vantage points. It also provides a mechanism for integrating the imagery obtained from the cameras with the measurements obtained from distributed sensors.
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