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Feasibility Study of Gabor Wavelet for Detection of Facial Expression: Facial Expression Recognition Based on Image Feature - Softcover

 
9783659459733: Feasibility Study of Gabor Wavelet for Detection of Facial Expression: Facial Expression Recognition Based on Image Feature

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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.

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About the Author

Qualification: Master In Engg.(Electronics & Telecommunication)HOD, Department of Electronics &Telecommunication, SVERI’s COE (Poly),Pandharpur.

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  • PublisherLAP LAMBERT Academic Publishing
  • Publication date2013
  • ISBN 10 3659459739
  • ISBN 13 9783659459733
  • BindingPaperback
  • LanguageEnglish
  • Number of pages88

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Taschenbuch. Condition: 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. Seller Inventory # 9783659459733

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Taschenbuch. Condition: 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. Seller Inventory # 9783659459733

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Taschenbuch. Condition: 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. Seller Inventory # 9783659459733

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Kumbhar, Mahesh; Jadhav, Ashish; Walunjkar, Mahesh; Kumbhar, Mahesh; Jadhav, Ashish; Walunjkar, Mahesh
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Kumbhar, Mahesh; Jadhav, Ashish; Walunjkar, Mahesh; Kumbhar, Mahesh; Jadhav, Ashish; Walunjkar, Mahesh
Published by Lap Lambert Academic Publishing, 2013
ISBN 10: 3659459739 ISBN 13: 9783659459733
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