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Human Recognition in Unconstrained Environments

Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics

  • 1st Edition - January 9, 2017
  • Editors: Maria De Marsico, Michele Nappi, Hugo Pedro Proença
  • Language: English
  • Hardback ISBN:
    9 7 8 - 0 - 0 8 - 1 0 0 7 0 5 - 1
  • eBook ISBN:
    9 7 8 - 0 - 0 8 - 1 0 0 7 1 2 - 9

Human Recognition in Unconstrained Environments provides a unique picture of the complete ‘in-the-wild’ biometric recognition processing chain; from data acquisition through t… Read more

Human Recognition in Unconstrained Environments

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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