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Intelligent Multimedia Analysis for Security Applications pp 79–95Cite as

Multiple Traits for People Identification

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 282))

Summary

Present biometric systems mostly rely on a single physical or behavioral feature for either identification or verification. However, day to day use of single biometries in massive or uncontrolled scenarios still has several shortcomings. These can be due to complex or unstable hardware settings, to changing environmental conditions or even to immature software procedures: some classification problems are intrinsically hard to solve. Possible spoofing of single biometric features is an additional issue. Last but not least, some features may occasionally lack the requisite of universality. As a consequence, biometric systems based on a single feature often have poor reliability, especially in applications where high security is needed.

Multimodal systems, i.e., systems that concurrently exploit multiple features, are a possible way to achieve improved effectiveness and reliability. There are several issues that must be addressed when designing such a system, including the choice of the set of biometric features, the normalization method, the integration schema and the fusion process, and the use of a measure of reliability for each subsystem on a single response basis. This chapter describes the state of the art regarding such issues and sketches some suggestions for future work.

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Author information

Authors and Affiliations

  1. DI — Dipartimento di Informatica, Università di Roma “La Sapienza”, Italy

    Maria De Marsico

  2. DMI — Dipartimento di Matematica e Informatica, Università di Salerno, Fisciano, (SA), Italy

    Riccardo Distasi, Michele Nappi & Daniel Riccio

Authors
  1. Maria De Marsico
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  2. Riccardo Distasi
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  3. Michele Nappi
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  4. Daniel Riccio
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Editor information

Editors and Affiliations

  1. TOBB ETÜ Computer Engineering Department, Sögütözü Cad.No:43, Sögütözü, 06560, Ankara, Turkey

    Husrev Taha Sencar

  2. Computing, Information Systems and Mathematics, Kingston University London, Penrhyn Road, KT1 2EE, Surrey, UK

    Sergio Velastin

  3. Department of Informatics, Aristotle University of Thessaloniki, Box 451, GR-54124, Thessaloniki, Greece

    Nikolaos Nikolaidis

  4. France Telecom R&D (Orange Labs) Beijing, Raycom Infotech Park C, 2 Science Institute South Road, Haidian District, 100080, Beijing, China

    Shiguo Lian

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De Marsico, M., Distasi, R., Nappi, M., Riccio, D. (2010). Multiple Traits for People Identification. In: Sencar, H.T., Velastin, S., Nikolaidis, N., Lian, S. (eds) Intelligent Multimedia Analysis for Security Applications. Studies in Computational Intelligence, vol 282. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11756-5_4

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  • DOI: https://doi.org/10.1007/978-3-642-11756-5_4

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  • Print ISBN: 978-3-642-11754-1

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