Unconstrained Face Recognition

Zhou, S. K.; Chellappa, Rama; Zhao, Wenyi

ISBN 10: 0387264078 / ISBN 13: 9780387264073

Published by Springer, New York, NY, 2006

About this Item

244 pp. Tightly bound. Corners not bumped. Text is free of markings. No ownership markings. Published without a dust jacket. Printed boards. The boards no longer show as glossy as when new. First Edition / First Printing. 9,8,7,6,5,4,3,2,1. This copy is smyth sewn. Smyth sewing is a method of bookbinding where groups of folded pages (referred to as signatures) are stitched together using binder thread. Each folded signature is sewn together individually with multiple stitches and then joined with other signatures to create the complete book block. This is the traditional and best method of bookbinding.

Seller Inventory # 032391

Bibliographic Details

• Title: Unconstrained Face Recognition
• Publisher: Springer, New York, NY
• Publication Date: 2006
• Language: English
• ISBN 10: 0387264078
• ISBN 13: 9780387264073
• Binding: Hardcover
• Edition: 1st Edition
• Condition: Very Good
• Dust Jacket Condition: Published Without Dust Jacket

About this title

Synopsis

Face recognition has been actively studied over the past decade and continues to be a big research challenge. Just recently, researchers have begun to investigate face recognition under unconstrained conditions. Unconstrained Face Recognition provides a comprehensive review of this biometric, especially face recognition from video, assembling a collection of novel approaches that are 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 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.