Similarity measures for face recognition / authored by Vezzetti, Enrico Marcolin, Federica Enrico Vezzetti and Federica Marcolin.

Format:

Book

Author/Creator:

Vezzetti, Enrico, author.

Marcolin, Federica, author.

Language:

English

Subjects (All):

Human face recognition (Computer science).

Physical Description:

1 online resource (108 p.)

Edition:

1st ed.

Place of Publication:

Sharjah, United Arab Emirates : Bentham Science Publishers, 2015.

Language Note:

English

Summary:

Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.

Contents:

Cover; Title; EUL; Contents; Foreword; Preface; Chapter 01; Chapter 02; Chapter 03; Chapter 04; Chapter 05; Chapter 06; Chapter 07; Chapter 08; Chapter 10; Chapter 11; References; Index

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

Description based on online resource; title from PDF title page (ebrary, viewed May 23, 2015).

ISBN:

9781681080444

1681080443

OCLC:

911246500