Camera sensors constitute an information rich sensing modality with many potential applications in sensor networks. Their effectiveness in a sensor network setting however greatly relies on their ability to calibrate with respect to each other, and other sensors in the field. This paper examines node localization and camera calibration using the shared field of view of camera pairs. Using a new distributed camera sensor network we compare two approaches from computer vision and propose an algorithm that combines a sparse set of distance measurements with image information to accurately localize nodes in 3D. Our algorithms are evaluated using a network of iMote2 nodes equipped with COTS camera modules. The sensor nodes identify themselves to cameras using modulated LED emissions. Our indoor experiments yielded a 2-7cm error in a 6x6m room. Our outdoor experiments in a 30x30m field resulted in errors 20-80cm, depending on the method used.

Although imaging is an information-rich sensing modality, the use of cameras in sensor networks is very often prohibited by factors such as power, computation cost, storage, communication bandwidth and privacy. In this paper we consider information selective and privacy-preserving address-event imagers for sensor networks. Instead of providing full images with a high degree of redundancy, our efforts in the design of these imagers specialize on selecting a handful of features from a scene and outputting these features in address-event representation. In this paper we present our initial results in modeling and evaluating address-event sensors in the context of sensor networks. Using three different platforms that we have developed, we illustrate how to model address-event cameras and how to build an emulator using these models. We also present a lightweight classification scheme to illustrate the computational advantages of address-event sensors. The paper concludes with an evaluation of the classification algorithm and a feasibility study of using COTS components to emulate address-event inside a sensor network.

The use of low-cost imagers in sensor network applications is imminent. Small low-power imagers have many potential applications in visual confirmation of events, target recognition, security and entertainment. To make the autonomous operation of imager sensors in such applications possible, smart imager sensors should be able to calibrate their views with respect to other imagers in the network and should become aware of the locations of other non-imager sensors. Such calibration will allow cameras with multiple vantage points and sensors distributed in physical space to jointly undertake collaborative tasks.