000 04248nam a22005535i 4500
001 978-0-85729-748-8
003 DE-He213
005 20140220083715.0
007 cr nn 008mamaa
008 130531s2011 xxk| s |||| 0|eng d
020 _a9780857297488
_9978-0-85729-748-8
024 7 _a10.1007/978-0-85729-748-8
_2doi
050 4 _aQA1-939
072 7 _aPB
_2bicssc
072 7 _aMAT000000
_2bisacsh
082 0 4 _a510
_223
100 1 _aPietikäinen, Matti.
_eauthor.
245 1 0 _aComputer Vision Using Local Binary Patterns
_h[electronic resource] /
_cby Matti Pietikäinen, Abdenour Hadid, Guoying Zhao, Timo Ahonen.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2011.
300 _aXVI, 212 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aComputational Imaging and Vision,
_x1381-6446 ;
_v40
505 0 _aBackground -- 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.
520 _aThe 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.
650 0 _aMathematics.
650 0 _aComputer vision.
650 0 _aOptical pattern recognition.
650 0 _aBiometrics.
650 1 4 _aMathematics.
650 2 4 _aMathematics, general.
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
650 2 4 _aImage Processing and Computer Vision.
650 2 4 _aPattern Recognition.
650 2 4 _aBiometrics.
650 2 4 _aSignal, Image and Speech Processing.
700 1 _aHadid, Abdenour.
_eauthor.
700 1 _aZhao, Guoying.
_eauthor.
700 1 _aAhonen, Timo.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780857297471
830 0 _aComputational Imaging and Vision,
_x1381-6446 ;
_v40
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-85729-748-8
912 _aZDB-2-SMA
999 _c105272
_d105272