Human Recognition In Unconstrained Environments: Using Computer Vision, Pattern Recognition And…

Hardcover | January 13, 2017

byMaria De MarsicoEditorMichele Nappi, Hugo Pedro Proen

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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

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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 Came...

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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 fundamentalsBackground subtraction of humans in outdoor scenescamera ...

Maria De Marsico is Associate Professor at Sapienza University of Rome, Department of Computes Science. She got her Master degree in Computer science from University of Salerno. Her scientific interests focus on Image Processing and Human Computer Interaction. Regarding the first one, she works on biometric recognition, including face,...

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Format:HardcoverDimensions:248 pages, 9.41 × 7.24 × 0.98 inPublished:January 13, 2017Publisher:Academic PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0081007051

ISBN - 13:9780081007051

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Table of Contents

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