Face Recognition & Principal Component Analysis Method: Algorithm, Simulation & Discussion - Couverture souple

Paul, Liton Chandra; Suman, Abdulla Al

9783659461453: Face Recognition & Principal Component Analysis Method: Algorithm, Simulation & Discussion

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ISBN 10 : 3659461458 ISBN 13 : 9783659461453

Editeur : LAP LAMBERT Academic Publishing, 2013

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This book mainly addresses the building of face recognition system and Principal Component Analysis (PCA) method in details. PCA is a statistical approach used for reducing the number of variables in face recognition. In PCA, every image in the training set is represented as a linear combination of weighted eigenvectors called eigenfaces. These eigenvectors are obtained from covariance matrix of a training image set called as basis function. The weights are found out after selecting a set of most relevant Eigenfaces. Recognition is performed by projecting a test image onto the subspace spanned by the eigenfaces and then classification is done by measuring Euclidean distance. A number of experiments were done to evaluate the performance of the face recognition system. Here, I used a training database of students of ETE-07 series, RUET, Rajshahi-6204, Bangladesh.

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�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2013
Langue: anglais
ISBN 10: 3659461458
ISBN 13: 9783659461453
Reliure: Broch�
Nombre de pages: 80
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Face Recognition & Principal Component Analysis Method : Algorithm, Simulation & Discussion

Liton Chandra Paul, Abdulla al Suman

Edit� par LAP LAMBERT Academic Publishing, 2013

ISBN 10 : 3659461458 ISBN 13 : 9783659461453

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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 80 | Sprache: Englisch | Produktart: B�cher. N� de r�f. du vendeur 24250535/2

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Face Recognition & Principal Component Analysis Method

Liton Chandra Paul|Abdulla al Suman

Edit� par LAP LAMBERT Academic Publishing, 2013

ISBN 10 : 3659461458 ISBN 13 : 9783659461453

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Paul Liton ChandraLiton Chandra Paul (Nominated for President Gold Medal,1st Class 1st With Honors) received B.Sc in ETE from RUET, Rajshahi, Bangladesh.Currently, he is working as a lecturer of ETE department at PUST, Pabna, Banglad. N� de r�f. du vendeur 5157518

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Face Recognition & Principal Component Analysis Method

Liton Chandra Paul

Edit� par LAP LAMBERT Academic Publishing Sep 2013, 2013

ISBN 10 : 3659461458 ISBN 13 : 9783659461453

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book mainly addresses the building of face recognition system and Principal Component Analysis (PCA) method in details. PCA is a statistical approach used for reducing the number of variables in face recognition. In PCA, every image in the training set is represented as a linear combination of weighted eigenvectors called eigenfaces. These eigenvectors are obtained from covariance matrix of a training image set called as basis function. The weights are found out after selecting a set of most relevant Eigenfaces. Recognition is performed by projecting a test image onto the subspace spanned by the eigenfaces and then classification is done by measuring Euclidean distance. A number of experiments were done to evaluate the performance of the face recognition system. Here, I used a training database of students of ETE-07 series, RUET, Rajshahi-6204, Bangladesh. 80 pp. Englisch. N� de r�f. du vendeur 9783659461453

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Face Recognition & Principal Component Analysis Method : Algorithm, Simulation & Discussion

Liton Chandra Paul

Edit� par LAP LAMBERT Academic Publishing, 2013

ISBN 10 : 3659461458 ISBN 13 : 9783659461453

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book mainly addresses the building of face recognition system and Principal Component Analysis (PCA) method in details. PCA is a statistical approach used for reducing the number of variables in face recognition. In PCA, every image in the training set is represented as a linear combination of weighted eigenvectors called eigenfaces. These eigenvectors are obtained from covariance matrix of a training image set called as basis function. The weights are found out after selecting a set of most relevant Eigenfaces. Recognition is performed by projecting a test image onto the subspace spanned by the eigenfaces and then classification is done by measuring Euclidean distance. A number of experiments were done to evaluate the performance of the face recognition system. Here, I used a training database of students of ETE-07 series, RUET, Rajshahi-6204, Bangladesh. N� de r�f. du vendeur 9783659461453

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Face Recognition & Principal Component Analysis Method

Liton Chandra Paul

Edit� par LAP LAMBERT Academic Publishing Sep 2013, 2013

ISBN 10 : 3659461458 ISBN 13 : 9783659461453

Neuf Taschenbuch

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book mainly addresses the building of face recognition system and Principal Component Analysis (PCA) method in details. PCA is a statistical approach used for reducing the number of variables in face recognition. In PCA, every image in the training set is represented as a linear combination of weighted eigenvectors called eigenfaces. These eigenvectors are obtained from covariance matrix of a training image set called as basis function. The weights are found out after selecting a set of most relevant Eigenfaces. Recognition is performed by projecting a test image onto the subspace spanned by the eigenfaces and then classification is done by measuring Euclidean distance. A number of experiments were done to evaluate the performance of the face recognition system. Here, I used a training database of students of ETE-07 series, RUET, Rajshahi-6204, Bangladesh.Books on Demand GmbH, �berseering 33, 22297 Hamburg 80 pp. Englisch. N� de r�f. du vendeur 9783659461453

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