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Advances in control engineering and material science made it possible to develop small-scale unmanned aerial vehicles (UAVs) equipped with cameras and sensors. These UAVs enable us to obtain a bird's eye view of the environment. Having access to an aerial view over large areas is helpful in disaster situations, where often only incomplete and inconsistent(More)
Having seen increased interest from the research community , smart camera systems have gone through a number of evolutionary steps like from single cameras to distributed smart camera systems with collaboration features. This work aims at defining a taxonomy to classify these systems based on their platform capabilities, the degree of distributed processing(More)
Two trends emerge in recent image processing research: distributed computing and embedded processing. Both trends are exempli¿ed in smart cameras which combine image sensing, image processing and communication on a single embedded device. Networks of distributed smart cameras help to overcome some hard problems that are inherent in single-camera systems.(More)
This paper reports on the integration of multi-camera tracking into an agent-based framework, which features autonomous task allocation for smart cameras targeting traffic surveillance. Since our target platforms are distributed embedded systems with limited resources, the trackers may only be active, if the target is in the camera's field of view.(More)
Unmanned aerial vehicles (UAVs) have been recently deployed in various civilian applications such as environmental monitoring, aerial imaging or surveillance. Small-scale UAVs are of special interest for first responders since they can rather easily provide bird's eye view images of disaster areas. In this paper we present a hybrid approach to mo-saick an(More)
In the recent past, much effort has been put into the development of distributed vision systems with smart cameras as key components. Smart cameras combine video sensing, processing and communication within a single embedded device and provide sufficient on-board infrastructure to carry out high-level video analysis tasks. Networks of smart cameras help to(More)
There is currently a strong trend towards the deployment of advanced computer vision methods on embedded systems. This deployment is very challenging since embedded platforms often provide limited resources such as computing performance , memory and power. In this paper we present a decentralized solution for tracking objects across multiple embedded smart(More)
—In this paper, we compare deterministic and prob-abilistic path planning strategies for an autonomous unmanned aerial vehicle (UAV) network, where the objective is to explore a given area with obstacles and provide an overview image. We present both online and offline implementations of the algorithms as alternative solutions, where applicable, and analyze(More)