×

Uh-oh, it looks like your Internet Explorer is out of date.

For a better shopping experience, please upgrade now.

Unconstrained Face Recognition
     

Unconstrained Face Recognition

by Shaohua Kevin Zhou, Rama Chellappa, Wenyi Zhao
 

See All Formats & Editions

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,

Overview

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.

Product Details

ISBN-13:
9781441938909
Publisher:
Springer US
Publication date:
11/29/2010
Series:
International Series on Biometrics , #5
Edition description:
Softcover reprint of hardcover 1st ed. 2006
Pages:
244
Product dimensions:
6.10(w) x 9.25(h) x 0.02(d)

Customer Reviews

Average Review:

Post to your social network

     

Most Helpful Customer Reviews

See all customer reviews