Computer Vision Using Local Binary Patterns (Computational Imaging and Vision)
| Author | : | |
| Rating | : | 4.97 (873 Votes) |
| Asin | : | 0857297473 |
| Format Type | : | paperback |
| Number of Pages | : | 212 Pages |
| Publish Date | : | 2015-03-26 |
| Language | : | English |
DESCRIPTION:
LBP Tomas B Good summary of LBP
The focus of this research has broadened from 2D textures to 3D textures and spatiotemporal (dynamic) textures. The book will also be of interest to all those who work with specific applications of machine vision.. 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. Computer Vision Using Local Binary Patterns provides a detailed description of the LBP methods and their variants both in spatial and spatiotemporal domains. 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
… 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. From the reviews:“This book will be of interest mainly to computer vision practitioners and other researchers interested in visual pattern recognition techniques. 54 (4), 2012) . It presents ‘local binary patterns’ and their many variants and applications