Automated Face Analysis: Emerging Technologies and Research

Automated Face Analysis: Emerging Technologies and Research

Indexed In: SCOPUS View 1 More Indices
Release Date: March, 2009|Copyright: © 2009 |Pages: 448
DOI: 10.4018/978-1-60566-216-9
ISBN13: 9781605662169|ISBN10: 160566216X|EISBN13: 9781605662176
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Description & Coverage
Description:

Since research on face recognition began in the 1960's, the field has rapidly widened to automated face analysis including face detection, facial gesture recognition, and facial expression recognition.

Automated Face Analysis: Emerging Technologies and Research provides theoretical background to understand the overall configuration and challenging problem of automated face analysis systems, featuring a comprehensive review of recent research for the practical implementation of the analysis system. A must-read for practitioners and students in the field, this book provides understanding by systematically dividing the subject into several subproblems such as detection, modeling, and tracking of the face.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • AdaBoost learning
  • Automated face analysis
  • Eye detection
  • Face certainty map
  • Face disguise discrimination
  • MCT-based feature correlation
  • Modified census transform
  • Robust eye detection
  • Role of face in human communication
Reviews & Statements

This book combines all related subjects such as face and eye detection, face modeling, face tracking, face recognition, facial expression recognition, and facial gesture recognition into one book, as well as, provides the introductory theoretical backgrounds for each subject.

– Daijin Kim, Pohang University of Science & Technology, Korea

This book surveys recent research in areas of the field such as face and eye detection, face modeling, and facial expression recognition, as well as related subjects such as hand-gesture and body-gesture recognition.

– Book News Inc. (June 2009)
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Editor/Author Biographies
Daijin Kim received the BS degree in electronic engineering from Yonsei University, Seoul, Korea, in 1981, and the MS degree in electrical engineering from the Korea Advanced Institute of Science and Technology(KAIST), Taejon, 1984. In 1991, he received the PhD degree in electrical and computer engineering from Syracuse University, Syracuse, NY. During 1992–1999, he was an Associate Professor in the Department of Computer Engineering at DongA University, Pusan, Korea. He is currently a Professor in the Department of Computer Science and Engineering at POSTECH, Pohang, Korea. His research interests include intelligent systems, biometrics, and Human Computer Interaction.
Jaewon Sung received his BS degree in computer engineering from Chungnam National University, Taejeon, Korea (2000) and his MS and PhD degrees in computer science and engineering from Pohang University of Science and Technology (POSTECH), Pohang, Korea (2002 and 2007, respectively). He was a postdoctoral researcher at POSTECH in 2007. He is currently a senior research engineer of LG electronics, Korea. His research interests include pattern recognition, machine vision, and video compression and coding.
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