Computer Vision Using Local Binary Patterns

Author:   Matti Pietikäinen ,  Abdenour Hadid ,  Guoying Zhao ,  Timo Ahonen
Publisher:   Springer London Ltd
Edition:   2011 ed.
Volume:   40
ISBN:  

9781447126652


Pages:   212
Publication Date:   03 August 2013
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Computer Vision Using Local Binary Patterns


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Overview

The recent emergence of Local Binary Patterns (LBP) has led to significant progress in applying texture methods to various computer vision problems and applications. The focus of this research has broadened from 2D textures to 3D textures and spatiotemporal (dynamic) textures. Also, where texture was once utilized for applications such as remote sensing, industrial inspection and biomedical image analysis, the introduction of LBP-based approaches have provided outstanding results in problems relating to face and activity analysis, with future scope for face and facial expression recognition, biometrics, visual surveillance and video analysis. Computer Vision Using Local Binary Patterns provides a detailed description of the LBP methods and their variants both in spatial and spatiotemporal domains. This comprehensive reference also provides an excellent overview as to how texture methods can be utilized for solving different kinds of computer vision and image analysis problems. Source codes of the basic LBP algorithms, demonstrations, some databases and a comprehensive LBP bibliography can be found from an accompanying web site. Topics include: local binary patterns and their variants in spatial and spatiotemporal domains, texture classification and segmentation, description of interest regions, applications in image retrieval and 3D recognition - Recognition and segmentation of dynamic textures, background subtraction, recognition of actions, face analysis using still images and image sequences, visual speech recognition and LBP in various applications. Written by pioneers of LBP, this book is an essential resource for researchers, professional engineers and graduate students in computer vision, image analysis and pattern recognition. The book will also be of interest to all those who work with specific applications of machine vision.

Full Product Details

Author:   Matti Pietikäinen ,  Abdenour Hadid ,  Guoying Zhao ,  Timo Ahonen
Publisher:   Springer London Ltd
Imprint:   Springer London Ltd
Edition:   2011 ed.
Volume:   40
Dimensions:   Width: 15.50cm , Height: 1.20cm , Length: 23.50cm
Weight:   0.355kg
ISBN:  

9781447126652


ISBN 10:   1447126653
Pages:   212
Publication Date:   03 August 2013
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Reviews

From the reviews: This book will be of interest mainly to computer vision practitioners and other researchers interested in visual pattern recognition techniques. It presents `local binary patterns' and their many variants and applications. ... this monograph is an accessible introduction to and survey of the local pattern approach to visual recognition by the group that has the most extensive experience with it. ... the book will be a valuable addition to the library of any specialist working in these areas. (Bill Triggs, SIAM Review, Vol. 54 (4), 2012)


From the reviews: This book will be of interest mainly to computer vision practitioners and other researchers interested in visual pattern recognition techniques. It presents 'local binary patterns' and their many variants and applications. ... this monograph is an accessible introduction to and survey of the local pattern approach to visual recognition by the group that has the most extensive experience with it. ... the book will be a valuable addition to the library of any specialist working in these areas. (Bill Triggs, SIAM Review, Vol. 54 (4), 2012)


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