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Self-Localizing Smart Camera Networks

机译：自定位智能相机网络

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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.
机译：本文介绍了一种新颖的方法来本地化嵌入式相机和传感器的网络。在此方案中，摄像机和传感器配备有可控光源（可见光或红外光），用于发出信号。然后，每个摄像机节点都可以自动确定从其有利位置可见的所有节点的方位。通过将这些测量值与从机载加速度计获得的测量值相融合，摄像机节点能够确定网络中其他节点的相对位置和方向。该方法使用从图像得出的角度测量值，而不是从飞行时间或信号衰减得出的距离测量值。该方案可以使用通用组件相对容易地实现，并且由于本地化计算利用了测量系统的稀疏结构，因此可以很好地扩展。另外，该方法提供了不能仅从范围测量中确定的照相机方向的估计。本地化技术可以用作构建更高级别应用程序的基本功能。该方法还可以用于基于从多个已注册有利位置获得的图像来自动调查感兴趣的传感器的位置，实施分布式监视系统或分析场景的结构。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结果进行整合。

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