Face Recognition Across the Imaging Spectrum

ISBN-13: 9783319803654 / Angielski / Miękka / 2019 / 383 str.

Thirimachos Bourlai

Opis

This authoritative text/reference presents a comprehensive review of algorithms and techniques for face recognition (FR), with an emphasis on systems that can be reliably used in operational environments. Insights are provided by an international team of pre-eminent experts into the processing of multispectral and hyperspectral face images captured under uncontrolled environments. These discussions cover a variety of imaging sensors ranging from state-of-the-art visible and infrared imaging sensors, to RGB-D and mobile phone image sensors. A range of different biometric modalities are also examined, including face, periocular and iris. This timely volume is a mine of useful information for researchers, practitioners and students involved in image processing, computer vision, biometrics and security.

Spis treści

An Overview of Spectral Imaging of Human Skin toward Face Recognition
David W. Allen

Collection of Multi-Spectral Biometric Data for Cross-Spectral Identification Applications
Jeremy M. Dawson, Seth C. Leffel, Cameron Whitelam, and Thirimachos Bourlai

Hyperspectral Face Databases for Facial Recognition Research
Woon Cho, Andreas Koschan, and Mongi A. Abidi

MWIR-to-Visible and LWIR-to-Visible Face Recognition Using Partial Least Squares and Dictionary Learning
Shuowen Hu, Nathaniel J. Short, Prudhvi K. Gurram, Kristan P. Gurton, and Christopher Reale

Local Operators and Measures for Heterogeneous Face Recognition
Zhicheng Cao, Natalia A. Schmid, and Thirimachos Bourlai

Assessment of Facial Recognition System Performance in Realistic Operating Environments
Kevin R. Leonard

Understanding Thermal Face Detection: Challenges and Evaluation
Janhavi Agrawal, Aishwarya Pant, Tejas I. Dhamecha, Richa Singh, and Mayank Vatsa

Face Recognition Systems under Spoofing Attacks
Ivana Chingovska, Nesli Erdogmus, André Anjos, and Sébastien Marcel

On the Effects of Image Alterations on Face Recognition Accuracy
Matteo Ferrara, Annalisa Franco, and Davide Maltoni

Document to Live Facial Identification
Antwan D. Clark, Cameron Whitelam, and Thirimachos Bourlai

Face Recognition in Challenging Environments: An Experimental and Reproducible Research Survey
Manuel Günther, Laurent El Shafey, and Sébastien Marcel

Face Recognition with RGB-D Images Using Kinect
Gaurav Goswami, Mayank Vatsa, and Richa Singh

Blending 2D and 3D Face Recognition
Massimo Tistarelli, Marinella Cadoni, Andrea Lagorio, and Enrico Grosso

Exploiting Score Distributions for Biometric Applications
Panagiotis Moutafis and Ioannis A. Kakadiaris

Multispectral Ocular Biometrics
Simona G. Crihalmeanu and Arun A. Ross

Blurb

This authoritative text/reference presents a comprehensive review of algorithms and techniques for face recognition (FR), with an emphasis on systems that can be reliably used in operational environments. Insights are provided by an international team of pre-eminent experts into the processing of multispectral and hyperspectral face images captured under uncontrolled environments. These discussions cover a variety of imaging sensors ranging from state-of-the-art visible and infrared imaging sensors, to RGB-D and mobile phone image sensors. A range of different biometric modalities are also examined, including face, periocular and iris.

Topics and features:

• Presents a detailed introduction to the spectral imaging of human skin, and describes the data collection of multispectral and hyperspectral face images
  
• Covers a range of face-based identification technologies addressing challenges in the processing of face images in visible and infrared spectral bands
  
• Provides an overview of spoofing attacks and counter-measures for FR systems, and analyzes the effects of digital image alterations on FR algorithms
  
• Investigates the processing of degraded face photographs from ID documents, and examines mobile FR in still images and video sequences
  
• Proposes a state-of-the-art RGB-D FR algorithm, and suggests algorithms for 3D-based FR as well as techniques blending 2D and 3D data
  
• Discusses score normalization methods, and explores the use of patterns in the sclera in order to improve the robustness of iris recognition systems
  

This timely volume is a mine of useful information for researchers, practitioners and students involved in image processing, computer vision, biometrics and security.

Dr. Thirimachos Bourlai is an Assistant Professor in the Lane Department of Computer Science and Electrical Engineering at West Virginia University, Morgantown, WV, USA.