Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659459739 ISBN 13: 9783659459733
Da: moluna, Greven, Germania
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Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659459739 ISBN 13: 9783659459733
Da: preigu, Osnabrück, Germania
EUR 35,60
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Feasibility Study of Gabor Wavelet for Detection of Facial Expression | Facial Expression Recognition Based on Image Feature | Mahesh Kumbhar (u. a.) | Taschenbuch | 88 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659459733 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: Lap Lambert Academic Publishing, 2013
ISBN 10: 3659459739 ISBN 13: 9783659459733
Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloPaperback. Condizione: Brand New. 88 pages. 8.66x5.91x0.20 inches. In Stock.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Sep 2013, 2013
ISBN 10: 3659459739 ISBN 13: 9783659459733
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 39,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book summarizes the use of Gabor wavelet in the facial expression recognition system. The recognition of facial expressions implies finding solutions to three distinct types of problems. The first one relates to detection of faces in the image. Once the face location is known, the second problem is the detection of the salient features within the facial areas. The final analysis consists by using any classification model and the extracted facial features will identify the correct facial expression. Gabor filter are used to extract the different features. The unique features for four classes (Ex. Happy, Sad, Surprise and Disgust) will be kept as a reference to the new input image. The new image features will apply to feed-forward neural networks (classifier) for recognition of four different facial expressions. In this study the Japanese Female Facial Expression (JAFFE) database used which contains expressers that expressed expressions. 88 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659459739 ISBN 13: 9783659459733
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 39,90
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book summarizes the use of Gabor wavelet in the facial expression recognition system. The recognition of facial expressions implies finding solutions to three distinct types of problems. The first one relates to detection of faces in the image. Once the face location is known, the second problem is the detection of the salient features within the facial areas. The final analysis consists by using any classification model and the extracted facial features will identify the correct facial expression. Gabor filter are used to extract the different features. The unique features for four classes (Ex. Happy, Sad, Surprise and Disgust) will be kept as a reference to the new input image. The new image features will apply to feed-forward neural networks (classifier) for recognition of four different facial expressions. In this study the Japanese Female Facial Expression (JAFFE) database used which contains expressers that expressed expressions.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Sep 2013, 2013
ISBN 10: 3659459739 ISBN 13: 9783659459733
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 39,90
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book summarizes the use of Gabor wavelet in the facial expression recognition system. The recognition of facial expressions implies finding solutions to three distinct types of problems. The first one relates to detection of faces in the image. Once the face location is known, the second problem is the detection of the salient features within the facial areas. The final analysis consists by using any classification model and the extracted facial features will identify the correct facial expression. Gabor filter are used to extract the different features. The unique features for four classes (Ex. Happy, Sad, Surprise and Disgust) will be kept as a reference to the new input image. The new image features will apply to feed-forward neural networks (classifier) for recognition of four different facial expressions. In this study the Japanese Female Facial Expression (JAFFE) database used which contains expressers that expressed expressions.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch.