Facial expressions convey non verbal cues, which play an important role in interpersonal relations. Automatic recognition of human face based on facial expression can be important component of natural human-machine interface. It may also be used in behavioral science. Although human can recognize the face practically without any effort, but reliable face recognition by machine is a challenge. This book presents a new approach for recognizing the face of a person considering the expression of the same human face at different instant of time. This methodology is developed combining Eigenface method for feature extraction and k-Means clustering for identification of the human face. In experimental purpose, AT&T face database is used which contains a set of 40 people with 10 images with different facial expressions at the different illumination. Experimental results demonstrate the efficacy of the approach. This book is written such a manner that it will help researchers to work on the area of image processing and pattern recognition. It also helps graduate students to know the background and basic theories of different face recognition methods.
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Soumen Bag received his B.E. and M.Tech degree in Computer Science & Engineering from NIT Durgapur, India in 2003 and 2008 respectively. At Present he has been a Research Scholar in IIT Kharagpur, India. His research interests are in Image Processing, OCR for Indian scripts, and Pattern Recognition. He is the author of 5 conference papers.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Facial expressions convey non verbal cues, which play an important role in interpersonal relations. Automatic recognition of human face based on facial expression can be important component of natural human-machine interface. It may also be used in behavioral science. Although human can recognize the face practically without any effort, but reliable face recognition by machine is a challenge. This book presents a new approach for recognizing the face of a person considering the expression of the same human face at different instant of time. This methodology is developed combining Eigenface method for feature extraction and k-Means clustering for identification of the human face. In experimental purpose, AT&T face database is used which contains a set of 40 people with 10 images with different facial expressions at the different illumination. Experimental results demonstrate the efficacy of the approach. This book is written such a manner that it will help researchers to work on the area of image processing and pattern recognition. It also helps graduate students to know the background and basic theories of different face recognition methods. 72 pp. Englisch. Seller Inventory # 9783843378307
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Facial expressions convey non verbal cues, which play an important role in interpersonal relations. Automatic recognition of human face based on facial expression can be important component of natural human-machine interface. It may also be used in behavioral science. Although human can recognize the face practically without any effort, but reliable face recognition by machine is a challenge. This book presents a new approach for recognizing the face of a person considering the expression of the same human face at different instant of time. This methodology is developed combining Eigenface method for feature extraction and k-Means clustering for identification of the human face. In experimental purpose, AT&T face database is used which contains a set of 40 people with 10 images with different facial expressions at the different illumination. Experimental results demonstrate the efficacy of the approach. This book is written such a manner that it will help researchers to work on the area of image processing and pattern recognition. It also helps graduate students to know the background and basic theories of different face recognition methods. Seller Inventory # 9783843378307
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bag SoumenSoumen Bag received his B.E. and M.Tech degree in Computer Science & Engineering from NIT Durgapur, India in 2003 and 2008 respectively. At Present he has been a Research Scholar in IIT Kharagpur, India. His research intere. Seller Inventory # 5467696
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Facial expressions convey non verbal cues, which play an important role in interpersonal relations. Automatic recognition of human face based on facial expression can be important component of natural human-machine interface. It may also be used in behavioral science. Although human can recognize the face practically without any effort, but reliable face recognition by machine is a challenge. This book presents a new approach for recognizing the face of a person considering the expression of the same human face at different instant of time. This methodology is developed combining Eigenface method for feature extraction and k-Means clustering for identification of the human face. In experimental purpose, AT&T face database is used which contains a set of 40 people with 10 images with different facial expressions at the different illumination. Experimental results demonstrate the efficacy of the approach. This book is written such a manner that it will help researchers to work on the area of image processing and pattern recognition. It also helps graduate students to know the background and basic theories of different face recognition methods.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch. Seller Inventory # 9783843378307
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Taschenbuch. Condition: Neu. An Efficient Human Face Recognition Approach | Combination of Eigenface and k-Means Clustering methods | Soumen Bag | Taschenbuch | 72 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783843378307 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 107180843