• Human Recognition in Unconstrained Environments; Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics (Hardback) 9780081007051
1 1
£75.49 GBP
£100.00 GBP £75.49 GBP
Sale Sold out
Free UK Shipping

Freshly Printed - allow 10 days lead

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

Learn to use computer vision, pattern recognition, and machine learning methods for biometrics in this discussion of the biometric recognition processing chain

Maria De Marsico (Edited by), Michele Nappi (Edited by), Hugo Pedro Proença (Edited by)

9780081007051

Hardback, published 13 January 2017

248 pages
23.4 x 19 x 2.1 cm, 0.67 kg

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

1. Iris Recognition on Mobile Devices Using Near-Infrared Images 2. Face recognition using dictionary learning and domain adaptation 3. Periocular Recognition in Non-ideal Images 4. Real Time 3D Face-Ear Recognition on Mobile Devices: New Scenarios for 3D Biometricks “in-the-Wild? 5. Fingerphoto Recognition in Outdoor Environment using Smartphones 6. Soft biometric labels in the wild. Case study on gender classification 7. Unconstrained data acquisition frameworks and protocols 8. Biometric Authentication to Access Controlled Areas through Eye Tracking 9. Non-cooperative biometrics: Cross-Jurisdictional concerns 10. Pattern Recognition and Machine Learning Methods for assessing the quality of fingerprints

Subject Areas: Image processing [UYT], Computer vision [UYQV]
View full details