Machine-based Intelligent Face Recognition

Machine-based Intelligent Face Recognition discusses the general engineering method of imitating intelligent human brains for video-based face recognition in a fundamental way, which is completely unsupervised, automatic, self-learning, self-updated and robust. It also overviews state-of-the-art research on cognitive-based biometrics and machine-based biometrics, and especially the advances in face recognition.

This book is intended for scientists, researchers, engineers, and students in the field of computer vision, machine intelligence, and particularly of face recognition.

Dr. Dengpan Mou, Dr.-Ing. and MSc from University of Ulm, Germany, is with Harman/Becker Automotive Systems GmbH, working on video processing, computer vision and machine learning research and development topics.

• Face Recognition
• HEP
• Intelligent Face Recognition
• Self-adaptive
• Self-learning

From the reviews:

“The aim of this book is to describe how one might construct an ideal face recognition system that is completely automatic; unsupervised; noninvasive, in the sense that no special requirements for poses or lighting are required; and robust, so that it works in an unconstrained environment, and manages pose shifts, occlusion, and lighting changes. … The book performs a valuable service by gathering together an overview of face recognition, including comprehensive bibliographies at the end of each chapter.” (J. P. E. Hodgson, ACM Computing Reviews, August, 2011)

• Harman/Becker Automotive Systems GmbH, D-76307, Karlsbad, Germany

  Dengpan Mou

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