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Human Recognition in Unconstrained Environments

Book Description

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

Table of Contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Contributors
  6. Editor Biographies
  7. Foreword
  8. Chapter 1: Unconstrained Data Acquisition Frameworks and Protocols
    1. Abstract
    2. 1.1. Introduction
    3. 1.2. Unconstrained Biometric Data Acquisition Modalities
    4. 1.3. Typical Challenges
    5. 1.4. Unconstrained Biometric Data Acquisition Systems
    6. 1.5. Conclusions
    7. References
  9. Chapter 2: Face Recognition Using an Outdoor Camera Network
    1. Abstract
    2. 2.1. Introduction
    3. 2.2. Taxonomy of Camera Networks
    4. 2.3. Face Association in Camera Networks
    5. 2.4. Face Recognition in Outdoor Environment
    6. 2.5. Outdoor Camera Systems
    7. 2.6. Remaining Challenges and Emerging Techniques
    8. 2.7. Conclusions
    9. References
  10. Chapter 3: Real Time 3D Face-Ear Recognition on Mobile Devices: New Scenarios for 3D Biometrics “in-the-Wild”
    1. Abstract
    2. 3.1. Introduction
    3. 3.2. 3D Capture of Face and Ear: CURRENT Methods and Suitable Options
    4. 3.3. Mobile Devices for Ubiquitous Face–Ear Recognition
    5. 3.4. The Next Step: Mobile Devices for 3D Sensing Aiming at 3D Biometric Applications
    6. 3.5. Conclusions and Future Scenarios
    7. References
  11. Chapter 4: A Multiscale Sequential Fusion Approach for Handling Pupil Dilation in Iris Recognition
    1. Abstract
    2. 4.1. Introduction
    3. 4.2. Previous Work
    4. 4.3. WVU Pupil Light Reflex (PLR) Dataset
    5. 4.4. Impact of Pupil Dilation
    6. 4.5. Proposed Method
    7. 4.6. Experimental Results
    8. 4.7. Conclusions and Future Work
    9. References
  12. Chapter 5: Iris Recognition on Mobile Devices Using Near-Infrared Images
    1. Abstract
    2. 5.1. Introduction
    3. 5.2. Preprocessing
    4. 5.3. Feature Analysis
    5. 5.4. Multimodal Biometrics
    6. 5.5. Conclusions
    7. References
  13. Chapter 6: Fingerphoto Authentication Using Smartphone Camera Captured Under Varying Environmental Conditions
    1. Abstract
    2. Acknowledgements
    3. 6.1. Introduction
    4. 6.2. Literature Survey
    5. 6.3. IIITD SmartPhone Fingerphoto Database v1
    6. 6.4. Proposed Fingerphoto Matching Algorithm
    7. 6.5. Experimental Results
    8. 6.6. Conclusion
    9. 6.7. Future Work
    10. References
  14. Chapter 7: Soft Biometric Attributes in the Wild: Case Study on Gender Classification
    1. Abstract
    2. 7.1. Introduction
    3. 7.2. Biometrics in the Wild
    4. 7.3. Gender Classification in the Wild
    5. 7.4. Conclusions
    6. References
  15. Chapter 8: Gait Recognition: The Wearable Solution
    1. Abstract
    2. 8.1. Machine Vision Approach
    3. 8.2. Floor Sensor Approach
    4. 8.3. Wearable Sensor Approach
    5. 8.4. Datasets Available for Experiments
    6. 8.5. An Example of a Complete System for Gait Recognition
    7. 8.6. Conclusions
    8. References
  16. Chapter 9: Biometric Authentication to Access Controlled Areas Through Eye Tracking
    1. Abstract
    2. 9.1. Introduction
    3. 9.2. ATM-Like Solutions
    4. 9.3. Methods Based on Fixation and Scanpath Analysis
    5. 9.4. Methods Based on Eye/Gaze Velocity
    6. 9.5. Methods Based on Pupil Size
    7. 9.6. Methods Based on Oculomotor Features
    8. 9.7. Methods Based on Head Orientation
    9. 9.8. Conclusions
    10. References
  17. Chapter 10: Noncooperative Biometrics: Cross-Jurisdictional Concerns
    1. Abstract
    2. 10.1. Introduction
    3. 10.2. Biometrics for Implementing Biometric Surveillance
    4. 10.3. Reaction to Public Opinion
    5. 10.4. The Early Days
    6. 10.5. An Interesting Clue (2007)
    7. 10.6. Biometric Surveillance Today
    8. 10.7. Conclusions
    9. References
  18. Index