Human Recognition in Unconstrained Environments: Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics


This book 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