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Design of multimedia surveillance systems

Published:14 August 2009Publication History
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Abstract

This article addresses the problem of how to select the optimal combination of sensors and how to determine their optimal placement in a surveillance region in order to meet the given performance requirements at a minimal cost for a multimedia surveillance system. We propose to solve this problem by obtaining a performance vector, with its elements representing the performances of subtasks, for a given input combination of sensors and their placement. Then we show that the optimal sensor selection problem can be converted into the form of Integer Linear Programming problem (ILP) by using a linear model for computing the optimal performance vector corresponding to a sensor combination. Optimal performance vector corresponding to a sensor combination refers to the performance vector corresponding to the optimal placement of a sensor combination. To demonstrate the utility of our technique, we design and build a surveillance system consisting of PTZ (Pan-Tilt-Zoom) cameras and active motion sensors for capturing faces. Finally, we show experimentally that optimal placement of sensors based on the design maximizes the system performance.

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  1. Design of multimedia surveillance systems

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    Idalia Flores

    In order to solve the problem of selecting the optimal combination of sensors and determining their optimal placement in a surveillance system, Sivaram, Kankanhalli, and Ramakrishnan design an integer programming model and explore some characteristics related to nonconvexity. The paper is divided into six sections. The first is an introduction, where the problem is well defined and established. Sections 2 and 3 present related work for the problem and the proposed technique. The technique consists of a performance vector whose elements represent the performance of subtasks, and a performance matrix that is presented with this vector. The performance vector corresponds to a sensor combination. As the problem is combinatorial, the integer linear model is useful for finding the optimal combination. Section 4 is devoted to the design of the surveillance system that consists of two types of sensors: infrared cameras and active motion sensors. The effect of the sensors and the cameras on the image capture subtask is modeled. This is an important section; it is very clear, but lacks a brief description of the combinatorial problem involved. Section 5 presents the results, but it doesn't explain the difficulty of working with nonconvex problems or offer statistics related to different experiments with the problem. The conclusions in the last section show the effectiveness of the technique based on the experimental results. Overall, the paper is clear and well organized. However, it would have been stronger if it had described the nonconvex nature of the problem and the computational complexity of the combinatorial problem, and given more details on the experiments. Online Computing Reviews Service

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    • Published in

      cover image ACM Transactions on Multimedia Computing, Communications, and Applications
      ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 5, Issue 3
      August 2009
      204 pages
      ISSN:1551-6857
      EISSN:1551-6865
      DOI:10.1145/1556134
      Issue’s Table of Contents

      Copyright © 2009 ACM

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 14 August 2009
      • Accepted: 1 May 2008
      • Revised: 1 March 2008
      • Received: 1 July 2007
      Published in tomm Volume 5, Issue 3

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