Human Recognition in Unconstrained Environments

Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics
by Maria De Marsico, Michele Nappi & Hugo Pedro Proença
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Publisher: Elsevier Science

Publication Date: January 09, 2017

ISBN: 9780081007129

Binding: Kobo eBook

Availability: eBook

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Human Recognition in Unconstrained Environments provides a unique picture of the complete ‘in-the-wild’ biometric recognition processing chain; from data acquisition through to detection, segmentation, encoding, and matching reactions against security incidents.

Coverage includes:

  • Data hardware architecture fundamentals

  • Background subtraction of humans in outdoor scenes

  • Camera synchronization

  • Biometric traits: Real-time detection and data segmentation

  • Biometric traits: Feature encoding / matching

  • Fusion at different levels

  • Reaction against security incidents

  • Ethical issues in non-cooperative biometric recognition in public spaces

  • With this book readers will learn how to:

  • Use computer vision, pattern recognition and machine learning methods for biometric recognition in real-world, real-time settings, especially those related to forensics and security

  • Choose the most suited biometric traits and recognition methods for uncontrolled settings

  • Evaluate the performance of a biometric system on real world data

  • Presents a complete picture of the biometric recognition processing chain, ranging from data acquisition to the reaction procedures against security incidents

  • Provides specific requirements and issues behind each typical phase of the development of a robust biometric recognition system

  • Includes a contextualization of the ethical/privacy issues behind the development of a covert recognition system which can be used for forensics and security activities