Handbook of Face Recognition

  • Stan Z. Li
  • Anil K. Jain

Table of contents

  1. Front Matter
    Pages I-X
  2. Stan Z. Li, Anil K. Jain
    Pages 1-11
  3. Stan Z. Li
    Pages 13-37
  4. Tim Cootes, Chris Taylor, Haizhuang Kang, Vladimir Petrović
    Pages 39-63
  5. Jörgen Ahlberg, Fadi Dornaika
    Pages 65-87
  6. Ronen Basri, David Jacobs
    Pages 89-111
  7. J. Birgitta Martinkauppi, Matti Pietikäinen
    Pages 113-135
  8. Gregory Shakhnarovich, Baback Moghaddam
    Pages 141-168
  9. Rama Chellappa, Shaohua Kevin Zhou
    Pages 169-192
  10. Ralph Gross, Simon Baker, Iain Matthews, Takeo Kanade
    Pages 193-216
  11. Sami Romdhani, Volker Blanz, Curzio Basso, Thomas Vetter
    Pages 217-245
  12. Ying-Li Tian, Takeo Kanade, Jeffrey F. Cohn
    Pages 247-275
  13. Zicheng Liu, Baining Guo
    Pages 277-300
  14. Ralph Gross
    Pages 301-327
  15. P. Jonathon Phillips, Patrick Grother, Ross Micheals
    Pages 329-348
  16. Thomas Huang, Ziyou Xiong, Zhenqiu Zhang
    Pages 371-390
  17. Back Matter
    Pages 391-395

About this book


Increased interest in face recognition stems from rising public concern for safety, the need for identity verification in the digital world, and the need for face analysis and modeling techniques in multimedia data management and computer entertainment.

This authoritative handbook is the first to provide complete coverage of face recognition, including major established approaches, algorithms, systems, databases, evaluation methods, and applications. After a thorough introductory chapter from the editors, 15 chapters address the sub-areas and major components necessary for designing operational face recognition systems. Each chapter focuses on a specific topic, reviewing background information, reviewing up-to-date techniques, presenting results, and offering challenges and future directions.

Features & Benefits:

*Provides comprehensive coverage of the main concepts, including face detection, tracking, alignment, feature extraction, and recognition

*Presents state-of-the-art methods and algorithms for designing face image-processing and recognition systems

*Examines design of secure, accurate, and reliable face recognition systems

*Describes performance evaluation methods and major applications, such as security, person verification, Internet communication, and computer entertainment

*Integrates numerous supporting graphs, tables, charts, and performance data

This accessible, practical reference is an essential resource for scientists and engineers, practitioners, government officials, and students planning to work in image processing, computer vision, biometrics and security, Internet communications, computer graphics, animation, and the computer game industry.

Stan Z. Li leads research programs in face detection and recognition, biometrics, and surveillance at Microsoft and is a senior member of the IEEE. Anil K. Jain is university-distinguished professor in the department of computer science and engineering at Michigan State University, as well as a fellow of the ACM, IEEE, and IAPR.


Key Topics:

Face detection, tracking, and alignment

Performance evaluation

Subspace analysis methods

Illumination and pose modeling

Morphable models of faces

Facial skin-color modeling

Face expression analysis and synthesis

Psychological and neural perspectives




-- Security / Pattern Recognition

-- Intermediate / Advanced


Computer Vision Face detection Face synthesis Face tracking Illumination modeling KLTcatalog Parametric modeling algorithms cognition image analysis pattern recognition

Authors and affiliations

  • Stan Z. Li
    • 1
  • Anil K. Jain
    • 2
  1. 1.Center for Biometrics Research and Testing & National Lab of Pattern Recognition Institute of AutomationChinese Academy of SciencesBeijingChina
  2. 2.Department of Computer Science & EngineeringMichigan State UniversityEast LansingUSA

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