Multibiometrics for Human Identification

doi:10.1017/CBO9780511921056

In today's security-conscious society, real-world applications for authentication or identification require a highly accurate system for recognizing individual humans. The required level of performance cannot be achieved through the use of a single biometric such as face, fingerprint, ear, iris, palm, gait or speech. Fusing multiple biometrics enables the indexing of large databases, more robust performance and enhanced coverage of populations. Multiple biometrics are also naturally more robust against attacks than single biometrics. This book addresses a broad spectrum of research issues on multibiometrics for human identification, ranging from sensing modes and modalities to fusion of biometric samples and combination of algorithms. It covers publicly available multibiometrics databases, theoretical and empirical studies on sensor fusion techniques in the context of biometrics authentication, identification and performance evaluation and prediction.

"Each chapter includes experimental results, references, and topics for future research. Anyone desiring an overview of contemporary multibiometric research in human identification will find this volume helpful."
Brad Reid, Computing Reviews

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Contents

Frontmatter
pp i-iv
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Contents
pp v-vi
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List of Contributors
pp vii-xii
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Preface
pp xiii-xiv
- By Bir Bhanu, University of California at Riverside, Venu Govindaraju, Center for Unified Biometrics and Sensors
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Introduction
pp 1-6
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PART I - MULTIMODAL AND MULTISENSOR BIOMETRIC SYSTEMS
pp 7-8
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1 - Multimodal Ear and Face Modeling and Recognition
pp 9-30
- By Steven Cadavid, University of Miami, Mohammad H. Mahoor, University of Denver, Mohamed Abdel-Mottaleb, University of Miami
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2 - Audiovisual Speech Synchrony Detection by a Family of Bimodal Linear Prediction Models
pp 31-50
- By Kshitiz Kumar, Carnegie Mellon University, Gerasimos Potamianos, Institute of Informatics and Telecommunications, Jiri Navratil, IBM TJ Watson Research Center, Etienne Marcheret, IBM TJ Watson Research Center, Vit Libal, Honeywell Prague Laboratory
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3 - Multispectral Contact-Free Palmprint Recognition
pp 51-73
- By Ying Hao, National Laboratory of Pattern Recognition, Zhenan Sun, National Laboratory of Pattern Recognition, Tieniu Tan, National Laboratory of Pattern Recognition
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4 - Face Recognition under the Skin
pp 74-92
- By Pradeep Buddharaju, University of Houston, Ioannis Pavlidis, University of Houston
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PART II - FUSION METHODS IN MULTIBIOMETRIC SYSTEMS
pp 93-94
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5 - Biometric Authentication: A Copula-Based Approach
pp 95-119
- By Satish G. Iyengar, Syracuse University, Pramod K. Varshney, Syracuse University, Thyagaraju Damarla, US Army Research Laboratory
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6 - An Investigation into Feature-Level Fusion of Face and Fingerprint Biometrics
pp 120-142
- By Ajita Rattani, University of Sassari, Massimo Tistarelli, Università di Sassari
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7 - Adaptive Multibiometric Systems
pp 143-170
- By Luca Didaci, University of Cagliari, Gian Luca Marcialis, University of Cagliari, Fabio Roli, University of Cagliari
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PART III - HYBRID BIOMETRIC SYSTEMS
pp 171-172
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8 - Multiple Projector Camera System for Three-Dimensional Gait Recognition
pp 173-205
- By Koichiro Yamauchi, Keio University, Bir Bhanu, University of California at Riverside, Hideo Saito, Keio University
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9 - Gait Recognition Using Motion Physics in a Neuromorphic Computing Framework
pp 206-234
- By Ricky J. Sethi, University of California, Los Angeles, Amit K. Roy-Chowdhury, University of California, Riverside, Ashok Veeraraghavan, Research Scientist Mitsubishi Electric Research Laboratories
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10 - Face Tracking and Recognition in a Camera Network
pp 235-257
- By Ming Du, University of Maryland, Aswin C. Sankaranarayanan, Rice University, Rama Chellappa, University of Maryland
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11 - Bidirectional Relighting for 3D-Aided 2D Face Recognition
pp 258-274
- By G. Toderici, University of Houston, G. Passalis, University of Houston, T. Theoharis, University of Houston, I. A. Kakadiaris, University of Houston
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PART IV - DATABASES AND SECURITY
pp 275-276
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12 - Acquisition and Analysis of a Dataset Comprising Gait, Ear, and Semantic Data
pp 277-301
- By Sina Samangooei, University of Southampton, John D. Bustard, University of Southampton, Richard D. Seely, University of Southampton, Mark S. Nixon, University of Southampton, John N. Carter, University of Southampton
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13 - Dynamic Security Management in Multibiometrics
pp 302-320
- By Ajay Kumar, The Hong Kong Polytechnic University
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PART V - PERFORMANCE OF MULTIBIOMETRIC SYSTEMS
pp 321-322
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14 - Prediction for Fusion of Biometrics Systems
pp 323-362
- By Rong Wang, Program Manager Pandigital Inc., Bir Bhanu, University of California at Riverside
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15 - Predicting Performance in Large-Scale Identification Systems by Score Resampling
pp 363-388
- By Sergey Tulyakov, Center for Unified Biometrics and Sensors, Venu Govindaraju, Center for Unified Biometrics and Sensors
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Plate section
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Multibiometrics for Human Identification

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Contents

Frontmatter
pp i-iv

Contents
pp v-vi

List of Contributors
pp vii-xii

Preface
pp xiii-xiv

Introduction
pp 1-6

PART I - MULTIMODAL AND MULTISENSOR BIOMETRIC SYSTEMS
pp 7-8

1 - Multimodal Ear and Face Modeling and Recognition
pp 9-30

2 - Audiovisual Speech Synchrony Detection by a Family of Bimodal Linear Prediction Models
pp 31-50

3 - Multispectral Contact-Free Palmprint Recognition
pp 51-73

4 - Face Recognition under the Skin
pp 74-92

PART II - FUSION METHODS IN MULTIBIOMETRIC SYSTEMS
pp 93-94

5 - Biometric Authentication: A Copula-Based Approach
pp 95-119

6 - An Investigation into Feature-Level Fusion of Face and Fingerprint Biometrics
pp 120-142

7 - Adaptive Multibiometric Systems
pp 143-170

PART III - HYBRID BIOMETRIC SYSTEMS
pp 171-172

8 - Multiple Projector Camera System for Three-Dimensional Gait Recognition
pp 173-205

9 - Gait Recognition Using Motion Physics in a Neuromorphic Computing Framework
pp 206-234

10 - Face Tracking and Recognition in a Camera Network
pp 235-257

11 - Bidirectional Relighting for 3D-Aided 2D Face Recognition
pp 258-274

PART IV - DATABASES AND SECURITY
pp 275-276

12 - Acquisition and Analysis of a Dataset Comprising Gait, Ear, and Semantic Data
pp 277-301

13 - Dynamic Security Management in Multibiometrics
pp 302-320

PART V - PERFORMANCE OF MULTIBIOMETRIC SYSTEMS
pp 321-322

14 - Prediction for Fusion of Biometrics Systems
pp 323-362

15 - Predicting Performance in Large-Scale Identification Systems by Score Resampling
pp 363-388

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Multibiometrics for Human Identification

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