Computer Vision Using Local Binary Patterns

Computer Vision Using Local Binary Patterns pdf epub mobi txt 电子书 下载 2025

出版者:Springer
作者:Matti Pietikäinen
出品人:
页数:222
译者:
出版时间:2011-7-8
价格:USD 99.00
装帧:Hardcover
isbn号码:9780857297471
丛书系列:
图书标签:
  • 计算机视觉 
  • 计算机科学 
  • 电子档 
  • 混口饭吃 
  • Vision 
  • Springer 
  • ComputerVision 
  • Computer 
  •  
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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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