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Similarity measures for face recognition
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Marcolin, Federica.
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Similarity measures for face recognition
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Similarity measures for face recognition/ Enrico Vezzetti and Federica Marcolin.
作者:
Vezzetti, Enrico.
其他作者:
Marcolin, Federica.
出版者:
Sharjah, U.A.E. :Bentham Science Publishers, : c2015.,
面頁冊數:
1 online resource :ill.
標題:
Face perception. -
電子資源:
https://doi.org/10.2174/97816810804441150101
ISBN:
9781681080444
Similarity measures for face recognition
Vezzetti, Enrico.
Similarity measures for face recognition
[electronic resource] /Enrico Vezzetti and Federica Marcolin. - 1st ed. - Sharjah, U.A.E. :Bentham Science Publishers,c2015. - 1 online resource :ill.
Includes bibliographical references and index.
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.
ISBN: 9781681080444Subjects--Topical Terms:
561965
Face perception.
LC Class. No.: TA1650
Dewey Class. No.: 006.3/7
Similarity measures for face recognition
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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.
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https://doi.org/10.2174/97816810804441150101
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