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    Полное описание

    Computer Vision Using Local Binary Patterns : монография / by Matti Pietikäinen, Abdenour Hadid, Guoying Zhao, Timo Ahonen. - London : Springer, 2011. - on-line. - (Computational Imaging and Vision, ISSN 1381-6446 ; vol. 40). - URL: http://dx.doi.org/10.1007/978-0-85729-748-8. - Загл. с экрана. - ISBN 978-0-85729-748-8. - Текст : электронный.
    Содержание:
    Background -- Local binary patterns for still images -- Spatiotemporal LBP -- 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 -- Face analysis using image sequences -- Visual recognition of spoken phrases -- LBP in different applications.

    ГРНТИ УДК
    55.30.33004.93

    Рубрики:
    mathematics
    computer graphics
    image processing
    pattern recognition
    biometrics (Biology)
    mathematics
    mathematics, general
    computer Imaging, Vision, Pattern Recognition and Graphics
    image Processing and Computer Vision
    pattern Recognition
    biometrics
    signal, Image and Speech Processing

    Аннотация: 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 - 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.
    Доп. точки доступа:
    Pietikäinen, M.
    Hadid, A.
    Zhao, G.
    Ahonen, T.

    http://dx.doi.org/10.1007/978-0-85729-748-8


    Держатели документа:
    Государственная публичная научно-техническая библиотека России : 123298, г. Москва, ул. 3-я Хорошевская, д. 17 (Шифр в БД-источнике (KATBW): -292360540)

    Шифр в сводном ЭК: 25b3ab490d378425761405ac4be183ef



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