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Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision
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Computer Vision Using Local Binary Patterns (Paperback, 2011 ed.)
Loot Price: R1,536
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Computer Vision Using Local Binary Patterns (Paperback, 2011 ed.)
Series: Computational Imaging and Vision, 40
Expected to ship within 10 - 15 working days
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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.
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