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Distributed Smart Cameras and Distributed Computer Vision

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Handbook of Signal Processing Systems

Abstract

Distributed smart cameras are multiple-camera systems that perform computer vision tasks using distributed algorithms. Distributed algorithms scale better to large networks of cameras than do centralized algorithms. However, new approaches are required to many computer vision tasks in order to create efficient distributed algorithms. This chapter motivates the need for distributed computer vision, surveys background material in traditional computer vision, and describes several distributed computer vision algorithms for calibration, tracking, and gesture recognition.

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Acknowledgements

This work was supported in part by the National Science Foundation under grant 0720536.

Author information

Authors and Affiliations

  1. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA

    Marilyn Wolf

  2. Department of Electrical Engineering, Princeton University, Princeton, NJ, USA

    Jason Schlessman

Authors
  1. Marilyn Wolf
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  2. Jason Schlessman
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Corresponding author

Correspondence to Marilyn Wolf .

Editor information

Editors and Affiliations

  1. Department of ECE and UMIACS, University of Maryland, College Park, MD, USA

    Shuvra S. Bhattacharyya

  2. Leiden Embedded Research Center, Leiden University Leiden Institute Advanced Computer Science, Leiden, The Netherlands

    Ed F. Deprettere

  3. RWTH Aachen University Software for Systems on Silicon, Aachen, Germany

    Rainer Leupers

  4. Department of Pervasive Computing, Tampere University of Technology, Tampere, Finland

    Jarmo Takala

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Wolf, M., Schlessman, J. (2019). Distributed Smart Cameras and Distributed Computer Vision. In: Bhattacharyya, S., Deprettere, E., Leupers, R., Takala, J. (eds) Handbook of Signal Processing Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-91734-4_10

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  • DOI: https://doi.org/10.1007/978-3-319-91734-4_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91733-7

  • Online ISBN: 978-3-319-91734-4

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