A Survey on Soft Biometrics for Human Identification


Book Description

The focus has been changed to multi-biometrics due to the security demands. The ancillary information extracted from primary biometric (face and body) traits such as facial measurements, gender, colour of the skin, ethnicity, and height is called soft biometrics and can be integrated to improve the speed and overall system performance of a primary biometric system (e.g., fuse face with facial marks) or to generate human semantic interpretation description (qualitative) of a person and limit the search in the whole dataset when using gender and ethnicity (e.g., old African male with blue eyes) in a fusion framework. This chapter provides a holistic survey on soft biometrics that show major works while focusing on facial soft biometrics and discusses some of the features of extraction and classification techniques that have been proposed and show their strengths and limitations.




Human Identification Using Soft Biometrics


Book Description

Humans naturally use descriptions to verbally convey the appearance of an individual. Eyewitness descriptions are an important resource for many criminal investigations. However, they cannot be used to automatically search databases featuring video or biometric data - reducing the utility of human descriptions in the search for the suspect. Soft biometrics are a new form of biometric identification which uses physical or behavioural traits that can be naturally described by humans. This thesis will explore how soft biometrics can be used alongside traditional biometrics, allowing video footage and biometric data to be searched using a description. To permit soft biometric identification the human description must be accurate, yet conventional descriptions comprising of absolute labels and estimations are often unreliable. A novel method of obtaining human descriptions will be introduced which utilizes comparative categorical labels to describe the differences between subjects. A database of facial and bodily comparative labels is introduced and analysed. Prior to use as a biometric feature, comparative descriptions must be anchored. Several techniques to convert multiple comparative labels into a single relative measurement are explored. Recognition experiments were conducted to assess the discriminative capabilities of relative measurements as a biometric. Relative measurements can also be obtained from other forms of human representation. This is demonstrated using several machine learning techniques to determine relative measurements from gait biometric signatures. Retrieval results are presented showing the ability to automatically search video footage using comparative descriptions.







Biometric Authentication


Book Description

This book constitutes the refereed proceedings of the First International Conference on Biometric Authentication, ICBA 2004, held in Hong Kong, China in July 2004. The 104 revised full papers presented were carefully reviewed and selected from 157 submissions; also included are summaries of 3 biometric competitions on fingerprint verification, face authentication, and signature verification. The papers are organized in topical sections on face, fingerprint, iris, signature, speech, biometric fusion and risk analysis, and other biometric issues.




Surveillance in Action


Book Description

This book addresses surveillance in action-related applications, and presents novel research on military, civil and cyber surveillance from an international team of experts. The first part of the book, Surveillance of Human Features, reviews surveillance systems that use biometric technologies. It discusses various novel approaches to areas including gait recognition, face-based physiology-assisted recognition, face recognition in the visible and infrared bands, and cross-spectral iris recognition. The second part of the book, Surveillance for Security and Defense, discusses the ethical issues raised by the use of surveillance systems in the name of combatting terrorism and ensuring security. It presents different generations of satellite surveillance systems and discusses the requirements for real-time satellite surveillance in military contexts. In addition, it explores the new standards of surveillance using unmanned air vehicles and drones, proposes surveillance techniques for detecting stealth aircrafts and drones, and highlights key techniques for maritime border surveillance, bio-warfare and bio-terrorism detection. The last part of the book, Cyber Surveillance, provides a review of data hiding techniques that are used to hinder electronic surveillance. It subsequently presents methods for collecting and analyzing information from social media sites and discusses techniques for detecting internal and external threats posed by various individuals (such as spammers, cyber-criminals, suspicious users or extremists in general). The book concludes by examining how high-performance computing environments can be exploited by malicious users, and what surveillance methods need to be put in place to protect these valuable infrastructures. The book is primarily intended for military and law enforcement personnel who use surveillance-related technologies, as well as researchers, Master’s and Ph.D. students who are interested in learning about the latest advances in military, civilian and cyber surveillance.







Machine Learning and Biometrics


Book Description

We are entering the era of big data, and machine learning can be used to analyze this deluge of data automatically. Machine learning has been used to solve many interesting and often difficult real-world problems, and the biometrics is one of the leading applications of machine learning. This book introduces some new techniques on biometrics and machine learning, and new proposals of using machine learning techniques for biometrics as well. This book consists of two parts: "Biometrics" and "Machine Learning for Biometrics." Parts I and II contain four and three chapters, respectively. The book is reviewed by editors: Prof. Jucheng Yang, Prof. Dong Sun Park, Prof. Sook Yoon, Dr. Yarui Chen, and Dr. Chuanlei Zhang.







Handbook of Digital Face Manipulation and Detection


Book Description

This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area.




Soft Computing for Recognition Based on Biometrics


Book Description

This book describes bio-inspired models and applications of hybrid intelligent systems using soft computing techniques for image analysis and pattern recognition based on biometrics and other sources. Each section groups papers on a similar subject.