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Simultaneous Detection and Tracking with Multiple Cameras

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Machine Learning for Computer Vision

Part of the book series: Studies in Computational Intelligence ((SCI,volume 411))

Abstract

Tracking targets using multiple cameras is an important processing step for applications such as sports analysis, traffic monitoring, behavior detection and event recognition. The multi-camera tracking problem has been mostly addressed in the literature as detection-based tracking: objects of interest (targets) are first detected and then associated over time [1]. Data from different cameras can be combined either after tracking (in track − first approaches) or before tracking (in fuse − first approaches).

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Authors and Affiliations

  1. Queen Mary University of London, London, UK

    Murtaza Taj & Andrea Cavallaro

Authors
  1. Murtaza Taj
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  2. Andrea Cavallaro
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Corresponding author

Correspondence to Murtaza Taj .

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Editors and Affiliations

  1. Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ, United Kingdom

    Roberto Cipolla

  2. Dipartimento di Matematica e Informatica, Università di Catania, Viale Andrea Doria 6, Catania, 95125, Catania, Italy

    Sebastiano Battiato

  3. Dipartimento di Matematica e Informatica, Università di Catania, Viale A. Doria 6, Catania, 95125, Italy

    Giovanni Maria Farinella

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Taj, M., Cavallaro, A. (2013). Simultaneous Detection and Tracking with Multiple Cameras. In: Cipolla, R., Battiato, S., Farinella, G. (eds) Machine Learning for Computer Vision. Studies in Computational Intelligence, vol 411. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28661-2_8

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  • DOI: https://doi.org/10.1007/978-3-642-28661-2_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28660-5

  • Online ISBN: 978-3-642-28661-2

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