A Decision-theoretic Approach to Dynamic Sensor Selection in Camera Networks

Matthijs T. J. Spaan and Pedro U. Lima. A Decision-theoretic Approach to Dynamic Sensor Selection in Camera Networks. In Int. Conf. on Automated Planning and Scheduling, pp. 279–304, 2009.


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Nowadays many urban areas have been equipped with networks of surveillance cameras, which can be used for automatic localization and tracking of people. However, given the large resource demands of imaging sensors in terms of bandwidth and computing power, processing the image streams of all cameras simultaneously might not be feasible. In this paper, we consider the problem of dynamical sensor selection based on user-defined objectives, such as maximizing coverage or improved localization uncertainty. We propose a decision-theoretic approach modeled as a POMDP, which selects k sensors to consider in the next time frame, incorporating all observations made in the past. We show how, by changing the POMDP's reward function, we can change the system's behavior in a straightforward manner, fulfilling the user's chosen objective. We successfully apply our techniques to a network of 10 cameras.

BibTeX Entry

  author =       {Matthijs T. J. Spaan and Pedro U. Lima},
  title =        {A Decision-theoretic Approach to Dynamic Sensor
                  Selection in Camera Networks},
  booktitle =    {Int.\ Conf.\ on Automated Planning and Scheduling},
  year =         2009,
  pages =        {279--304}

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