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Handbook of Face RecognitionMarch 2005
Publisher:
  • Springer-Verlag
  • Berlin, Heidelberg
ISBN:978-0-387-40595-7
Published:01 March 2005
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Abstract

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Contributors
  • Michigan State University

Reviews

Markus Burki

Heightened concern for public safety and the need for reliable identity verification based on facial features have increased the interest in automatic face recognition systems. This book describes recent research in areas of interest to face recognition researchers. The intended audience for this book is professionals and students interested in state-of-the-art face recognition. This book also provides references for scientists and engineers working in related fields. The authors give readers an in-depth overview of the history of face recognition and compare various approaches, including very recent developments. The book does assume some familiarity with the topic, and the beginner may find it difficult to follow at times. Some shortcomings include the book's fairly limited index, and the fact that the table of contents only lists the main chapters, making it difficult to quickly navigate through the book. The book covers all major components and subareas of designing operational face recognition systems. Each chapter describes a specific system component by introducing background information on the topic, reviewing up-to-date research, and presenting an outlook for future development. In chapter 1, the authors give an overview of face recognition processing from face detection, tracking, alignment, and feature extraction. Chapter 2 discusses face detection techniques in greater detail, and reviews effective learning methods. Chapters 3 and 4 describe face modeling methods for face alignment, where the input images may come from static images or video sequences. In chapters 5 and 6, the authors discuss methods that improve recognition performance under varying illumination, and use facial skin color modeling, where color is used. Chapter 7 provides insight on subspace modeling and learning-based dimension-reducing methods. Chapter 8 shows techniques for face tracking and recognition from video images. Chapters 9 and 10 cover methods for pose and illumination normalization, and extraction of facial features using a fairly new method called morphable models. Chapters 11 and 12 describe methods for facial expression analysis and synthesis. Chapter 13 takes a look at several publicly available databases for face recognition, face detection, and facial expression analysis. Chapter 14 discusses techniques for evaluating the performance of a facial recognition system. Chapter 15 describes how the human brain might perform such a task from a psychological and neural perspective, and chapter 16 discusses various face recognition applications. I highly recommend this book to anyone interested in learning more about the field of face recognition. Even if you are new to the field, you will gain some interesting insight into its history and the very latest face recognition research. Online Computing Reviews Service

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