Dynamic Computer Vision: From Images to Face Recognition Through Mathematical and Computer Algorithms - Softcover
Synopsis
This book focuses primarily on the development of orthoface for recognition. Orthoface method transforms faces from image space to face space. It achieves a dimension reduction similar to that of eigenface. All of the classification methods applicable to eigenface method can be applied to the orthoface method without any further modification. It maximises the inter-class scattering, and minimizes the intra-class scattering, which has been the weakness of the conventional eigenface method. The project matrix of the training face from the orthoface method forms an upper-triangular matrix. Each training face has a different number of coefficients allowing better discrimination and classification. The classification technique improves recognition speed significantly. This book also focuses on pose-invariant face recognition. This part concentrates on the use of a 3D head model and texture mapping technique to derive new pose views from one or two existing views, which is realised through the use of a deformable 3D head model. Deformation is done via parameters extracted from various feature measurements. The facial texture is mapped onto the 3D surface using cylinder texture mapping.
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Dynamic Computer Vision
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Scholars' Press Feb 2015, 2015
ISBN 10: 3639761588
ISBN 13: 9783639761580
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book focuses primarily on the development of orthoface for recognition. Orthoface method transforms faces from image space to face space. It achieves a dimension reduction similar to that of eigenface. All of the classification methods applicable to eigenface method can be applied to the orthoface method without any further modification. It maximises the inter-class scattering, and minimizes the intra-class scattering, which has been the weakness of the conventional eigenface method. The project matrix of the training face from the orthoface method forms an upper-triangular matrix. Each training face has a different number of coefficients allowing better discrimination and classification. The classification technique improves recognition speed significantly. This book also focuses on pose-invariant face recognition. This part concentrates on the use of a 3D head model and texture mapping technique to derive new pose views from one or two existing views, which is realised through the use of a deformable 3D head model. Deformation is done via parameters extracted from various feature measurements. The facial texture is mapped onto the 3D surface using cylinder texture mapping. 212 pp. Englisch. Seller Inventory # 9783639761580
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Dynamic Computer Vision
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rashid Syed ZahidurHe works as an instructor at IUc. He studied M.Sc. in Computer Science and Engineering, also B.Sc. in Computer Science & Communication Engineering at IUc. His research interests are computer vision & pattern recogn. Seller Inventory # 17682867
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Dynamic Computer Vision | From Images to Face Recognition Through Mathematical and Computer Algorithms
Print on DemandSeller: preigu, Osnabrück, Germany
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Taschenbuch. Condition: Neu. Dynamic Computer Vision | From Images to Face Recognition Through Mathematical and Computer Algorithms | Syed Zahidur Rashid | Taschenbuch | 212 S. | Englisch | 2015 | Scholars' Press | EAN 9783639761580 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 104836949
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Dynamic Computer Vision
Published by
Scholars' Press Feb 2015, 2015
ISBN 10: 3639761588
ISBN 13: 9783639761580
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -This book focuses primarily on the development of orthoface for recognition. Orthoface method transforms faces from image space to face space. It achieves a dimension reduction similar to that of eigenface. All of the classification methods applicable to eigenface method can be applied to the orthoface method without any further modification. It maximises the inter-class scattering, and minimizes the intra-class scattering, which has been the weakness of the conventional eigenface method. The project matrix of the training face from the orthoface method forms an upper-triangular matrix. Each training face has a different number of coefficients allowing better discrimination and classification. The classification technique improves recognition speed significantly. This book also focuses on pose-invariant face recognition. This part concentrates on the use of a 3D head model and texture mapping technique to derive new pose views from one or two existing views, which is realised through the use of a deformable 3D head model. Deformation is done via parameters extracted from various feature measurements. The facial texture is mapped onto the 3D surface using cylinder texture mapping.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 212 pp. Englisch. Seller Inventory # 9783639761580
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Dynamic Computer Vision : From Images to Face Recognition Through Mathematical and Computer Algorithms
Print on DemandSeller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book focuses primarily on the development of orthoface for recognition. Orthoface method transforms faces from image space to face space. It achieves a dimension reduction similar to that of eigenface. All of the classification methods applicable to eigenface method can be applied to the orthoface method without any further modification. It maximises the inter-class scattering, and minimizes the intra-class scattering, which has been the weakness of the conventional eigenface method. The project matrix of the training face from the orthoface method forms an upper-triangular matrix. Each training face has a different number of coefficients allowing better discrimination and classification. The classification technique improves recognition speed significantly. This book also focuses on pose-invariant face recognition. This part concentrates on the use of a 3D head model and texture mapping technique to derive new pose views from one or two existing views, which is realised through the use of a deformable 3D head model. Deformation is done via parameters extracted from various feature measurements. The facial texture is mapped onto the 3D surface using cylinder texture mapping. Seller Inventory # 9783639761580