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Real-Time Vision Tracking Algorithm

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Computational Science and Its Applications - ICCSA 2006 (ICCSA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3984))

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Abstract

Real-time object tracking is recently becoming very important in many video processing tasks. Applications like video surveillance, robotics, people tracking, etc., need reliable and economically affordable video tracking tools. Most of current available solutions are, however, computationally intensive and sometimes require expensive video hardware. In this paper, we propose a new object tracking algorithm for real-time video that relies in the combination of a similarity measure with an euclidian metric. This approach infers the trajectory of a moving object by applying a very simple optimization method which makes the tracking algorithm robust and easy to implement. Experimental results are provided to demonstrate the performance of the proposed tracking algorithm in complex real-time video sequence scenarios.

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Author information

Authors and Affiliations

  1. Facultad de Ciencias, UASLP, Av. Dr. Salvador Nava s/n, Zona Universitaria, C.P. 78290, San Luis Potosi, S.L.P., Mexico

    Edgar R. Arce-Santana, Jose M. Luna-Rivera, Daniel U. Campos-Delgado & Ulises Pineda-Rico

Authors
  1. Edgar R. Arce-Santana
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  2. Jose M. Luna-Rivera
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  3. Daniel U. Campos-Delgado
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  4. Ulises Pineda-Rico
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary,, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  2. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. OptimaNumerics Ltd.,, Cathedral House 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

  5. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  6. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  7. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  8. School of Information and Communication Engineering, Sungkyunkwan University, Korea

    Hyunseung Choo

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© 2006 Springer-Verlag Berlin Heidelberg

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Arce-Santana, E.R., Luna-Rivera, J.M., Campos-Delgado, D.U., Pineda-Rico, U. (2006). Real-Time Vision Tracking Algorithm. In: Gavrilova, M.L., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3984. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751649_45

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  • DOI: https://doi.org/10.1007/11751649_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34079-9

  • Online ISBN: 978-3-540-34080-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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