A.O. Ercan, A. El Gamal and L.J. Guibas, Camera network node selection for target localization in the presence of occlusions, Proc. ACM SenSys Workshop on Distributed Smart Cameras 2006.

Abstract:

A camera network node subset selection methodology for target localization in the presence of static and moving occluders is described. It is assumed that the locations of the static occluders are known, but that only prior statistics for the positions of the object and the moving occluders are available. This occluder information is captured in the camera measurement via an indicator random variable that takes the value 1 if the camera can see the object and 0, otherwise. The minimum MSE of the best linear estimate of object position based on camera measurements is then used as a metric for selection. It is shown through simulations and experimentally that a greedy selection heuristic performs close to optimal and outperforms other heuristics.

Bibtex: 

@inproceedings{eeg-cnnstlpo-06,
     author="A.O. Ercan and A. El Gamal and L. Guibas", 
     title="Camera network node selection for target localization in the presence of occlusions", 
     booktitle="ACM SenSys Workshop on Distributed Smart Cameras",
     month="November", 
     year="2006",
}