Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)

Graduate Group

Computer and Information Science

First Advisor

Camillo J. Taylor


As the prices of cameras and computing elements continue to fall, it

has become increasingly attractive to consider the deployment of

smart camera networks. These networks would be composed of small,

networked computers equipped with inexpensive image sensors. Such

networks could be employed in a wide range of applications including

surveillance, robotics and 3D scene reconstruction.

One critical problem that must be addressed before such systems can

be deployed effectively is the issue of localization. That is, in

order to take full advantage of the images gathered from multiple

vantage points it is helpful to know how the cameras in the scene

are positioned and oriented with respect to each other. To address

the localization problem we have proposed a novel approach to

localizing networks of embedded cameras and sensors. In this scheme

the cameras and the nodes are equipped with controllable light

sources (either visible or infrared) which are used for

signaling. Each camera node can then automatically determine the

bearing to all 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.

This localization technology can serve as a basic capability on

which higher level applications can be built. The method could 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 the 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.

We have successfully used our custom made self localizing smart

camera networks to implement a novel decentralized target tracking

algorithm, create an ad-hoc range finder and localize the components

of a self assembling modular robot.

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