Unconstrained Face Recognition

Zhou, Shaohua Kevin; Chellappa, Rama; Zhao, Wenyi

ISBN 10: 1441938907 / ISBN 13: 9781441938909

Published by Springer, 2010

About this Item

Seller Inventory # 12688380-n

Bibliographic Details

• Title: Unconstrained Face Recognition
• Publisher: Springer
• Publication Date: 2010
• Language: English
• ISBN 10: 1441938907
• ISBN 13: 9781441938909
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Face recognition has been actively studied recently, and continues to be a big research challenge. Just recently, researchers have begun to investigate face recognition under unconstrained conditions. This is a comprehensive review of the facial biometric, especially face recognition from video. The underlying basis of these approaches is that, unlike conventional face recognition algorithms, they exploit the inherent characteristics of the unconstrained situation and thus improve the recognition performance when compared with conventional algorithms. Unconstrained Face Recognition is structured to meet the needs of a professional audience of researchers and practitioners in industry. This volume is also suitable for advanced-level students in computer science.

From the Back Cover

Although face recognition has been actively studied over the past decade, the state-of-the-art recognition systems yield satisfactory performance only under controlled scenarios. Recognition accuracy degrades significantly when confronted with unconstrained situations. Examples of unconstrained conditions include illumination and pose variations, video sequences, expression, aging, and so on. Recently, researchers have begun to investigate face recognition under unconstrained conditions that is referred to as unconstrained face recognition.

This volume provides a comprehensive view of unconstrained face recognition, especially face recognition from multiple still images and/or video sequences, assembling a collection of novel approaches able to recognize human faces under various unconstrained situations. The underlying basis of these approaches is that, unlike conventional face recognition algorithms, they exploit the inherent characteristics of the unconstrained situation and thus improve the recognition performance when compared with conventional algorithms. Unconstrained Face Recognition is accessible to a wide audience with an elementary level of linear algebra, probability and statistics, and signal processing.

Unconstrained Face Recognition is designed primarily for a professional audience composed of practitioners and researchers working within face recognition and other biometrics. Also instructors can use the book as a textbook or supplementary reading material for graduate courses on biometric recognition, human perception, computer vision, or other relevant seminars.