Xiaoye Jiang, Mo Li, Yuan Yao, and Leonidas Guibas. Overcomplete Radon Bases for Target Property Management in Sensor Networks. The Tenth International Conference on Information Processing in Sensor Networks (IPSN). Chicago, USA, April 2011.

Abstract:

This paper presents a scalable algorithm for managing property information about moving objects tracked by a sensor network. Property information is obtained via distributed sensor observations, but will be corrupted when objects mix up with each other. The association between properties and objects then becomes ambiguous. We build a novel representation framework, exploiting an overcomplete Radon basis dictionary to model property uncertainty in such circumstances. By making use of the combinatorial structure of the basis design and sparse representations we can efficiently approximate the underlying probability distribution of the association between target properties and tracks, overcoming the exponential space that would otherwise be required. We conduct comparative simulations and the results validate the effectiveness of our approach.

Bibtex: 

@inproceedings{jlyg-uorb-11,
title = {Overcomplete Radon Bases for Target Property Management in Sensor Networks},
author = {Xiaoye Jiang and Mo Li and Yuan Yao and Leonidas Guibas},
booktitle = {In Proceedings of the 10th International Conference on Information Processing in Sensor Networks (IPSN)},
year = 2011,
month = {April},
address = {Chicago, Illinois},
wwwfilebase = {ipsn2011-jiang-li-yao-guibas},
wwwtopic = {Sensor Networks},
}