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Signal and Image Processing for Biometrics pp 285–331Cite as

Human Tracking in Non-cooperative Scenarios

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 292))

Abstract

In this chapter we discuss human tracking problems for biometric applications in non-cooperative scenarios. The chapter starts with an overview of modern biometric authentication systems. Special attention is paid to vision system construction and its design fundamentals. Next the existing image segmentation methods are presented with emphasis on procedures suitable for image pre-segmentation during the acquisition process. The chapter ends with some sample processing architectures presentation.

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Notes

  1. 1.

    http://www.oki.com/en/iris/

  2. 2.

    http://www.birger.com/

  3. 3.

    Motion blob—region in the image corresponding to moving object.

  4. 4.

    http://homepages.inf.ed.ac.uk/rbf/CAVIAR/

  5. 5.

    The equation is given for scalar \(X_t\) values. In high dimensional spaces with full covariance matrices, it is sometimes advantageous to use a constant learning rate \(\rho \) to simplify computations and provide faster model adaptation.

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Authors and Affiliations

  1. Department of Microelectronics and Computer Science, Lodz University of Technology, Wolczanska 221/223, 90-924, Lodz, Poland

    Kamil Grabowski & Wojciech Sankowski

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  1. Kamil Grabowski
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  2. Wojciech Sankowski
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Correspondence to Wojciech Sankowski .

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Editors and Affiliations

  1. Federal University of Rio Grande do Sul, Porto Alegre, Brazil

    Jacob Scharcanski

  2. IT-Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal

    Hugo Proença

  3. Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, USA

    Eliza Du

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Grabowski, K., Sankowski, W. (2014). Human Tracking in Non-cooperative Scenarios. In: Scharcanski, J., Proença, H., Du, E. (eds) Signal and Image Processing for Biometrics. Lecture Notes in Electrical Engineering, vol 292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54080-6_11

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  • DOI: https://doi.org/10.1007/978-3-642-54080-6_11

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  • Online ISBN: 978-3-642-54080-6

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