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 scenes Camera synchronizationBiometric traits: Real-time detection and data segmentationBiometric traits: Feature encoding / matching Fusion at different levelsReaction against security incidentsEthical 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 securityChoose the most suited biometric traits and recognition methods for uncontrolled settingsEvaluate the performance of a biometric system on real world data
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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, iris, gate, and multimodal recognition. Regarding the second one, she is especially interested in multimodal interaction, accessibility for users with special needs, and advanced techniques for personalized distance learning. She is Associate Editor of Pattern Recognition Letters, and Area Editor of the IEEE Biometrics Compendium. She published about 100 scientific works in international journals, conferences, and book chapters. She has been member of many Technical program Committees and is referee for several top journals, and Program Chair for the International Conference on Pattern Recognition Applications and Methods since 2013.
Michele Nappi received the laurea degree (cum laude) in computer science from the University of Salerno, Salerno, Italy, in 1991, the M.Sc. degree in information and communication technology from I.I.A.S.S. "E.R. Caianiello", Vietri sul Mare, Salerno, and the Ph.D. degree in applied mathematics and computer science from the University of Padova, Padova, Italy. He is currently an Associate Professor of computer science at the University of Salerno.
His research interests include Multibiometric Systems, Pattern Recognition, Image Processing, Compression and Indexing, Multimedia Databases, Human-Computer Interaction, VR/AR. He co-authored over 120 papers in international conference, peer review journals and book chapters in these fields (see http: //www.informatik.uni-trier.de/ ley/pers/hd/n/Nappi: Michele.html). He also served as Guest Editor for several international journals and as Editor for International Books. In 2014 He was one of the founders of the spin off BS3 (Biometric System for Security and Safety). President of the Italian Chapter of the IEEE Biometrics Council (2015-2017), member of IAPR and IEEE, He is team leader of the Biometric and Image Processing Lab (BIPLAB). Dr. Nappi received several international awards for scientific and research activities.
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 248 pp. Englisch. N° de réf. du vendeur 9780081007051
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