Please use this identifier to cite or link to this item: https://doi.org/10.1109/PERCOM.2009.4912836
Title: Resource constrained particle filtering for real-time multi-target tracking in sensor networks
Authors: Ong, L.-L. 
Xiao, W.
Tham, C.-K. 
Ang Jr., M.H. 
Issue Date: 2009
Source: Ong, L.-L.,Xiao, W.,Tham, C.-K.,Ang Jr., M.H. (2009). Resource constrained particle filtering for real-time multi-target tracking in sensor networks. 7th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2009 : -. ScholarBank@NUS Repository. https://doi.org/10.1109/PERCOM.2009.4912836
Abstract: This paper introduces methods for allocating com putational resources to track multiple targets in a sensor network of cameras, with the aim of maximizing tracking accuracy, an aspect of information quality (IQ). Particle filters are used where an independent fitter is created for each target track. The particle filter's strength to track complex probability models comes at the cost of a higher demand for computational resources. As there is a direct correlation between the number of particles used and the computational costs, a means to meet the computational resource constraints is to limit the total number of particles. This motivates an online distribution of available particles to available tracks to maximise tracking accuracy. Restricting the number of particles may result in ineffective particle filters that diverge from the true target position. This issue has not been addressed in any known work of allocating particles. Our solution is a particle allocation scheme that allocates available particles to existing tracks based on both filter uncertainty and the effectiveness of the particle sample set. A method to allocate assigned particles in a track to overcome suspected divergence is also applied. Experimental results, from a multi.target tracking simulation, show that given the same number of particles to allocate, our scheme outperforms two other methods, which are (a) an equal (fixed) allocation of particles to each filter and (b) an allocation of particles solely based on filter uncertainty. © 2009 IEEE.
Source Title: 7th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2009
URI: http://scholarbank.nus.edu.sg/handle/10635/71629
ISBN: 9781424433049
DOI: 10.1109/PERCOM.2009.4912836
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