000			04075cam a22005057i 4500
001			20044527
003			OSt
005			20210517143953.0
008			171003s2017 caua b 001 0 eng d
010			_a 2016439939
020			_a9781491937990
020			_a1491937998
035			_a(OCoLC)ocn968936315
037			_bOreilly & Associates Inc, C/O Ingram Pub Services 1 Ingram Blvd, LA Vergne, TN, USA, 37086 _nSAN 631-8673
040			_aSXP _beng _cSXP _erda _dSXP _dJRZ _dOQX _dOCLCF _dYDX _dOCLCQ _dCLU _dUNBCA _dBDX _dOCL _dSFR _dDLC
042			_alccopycat
050	0	0	_aTA1634 _b.K34 2017
082	0	4	_a8850 _bTA 1634 .K34 2017
100	1		_aKaehler, Adrian, _eauthor.
245	1	0	_aLearning OpenCV 3 : _bcomputer vision in C++ with the OpenCV library / _cAdrian Kaehler and Gary Bradski.
246	3	0	_aOpenCV
246	3	0	_aComputer vision in C++ with the OpenCV library
250			_aFirst edition, Second release.
264		1	_aSebastopol, CA : _bO'Reilly Media, _c[2017]
264		4	_c©2017
300			_axxv, 990 pages : _billustrations ; _c24 cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references (pages 949-965) and index.
505	0		_a1. Overview -- 2. Introduction to OpenCV -- 3. Getting to know OpenCV data types -- 4. Images and Large Array Types -- 5. Array Operations -- 6. Drawing and Annotating -- 7. Functors in OpenCV -- 8. Image, Video, and Data Files -- 9. Cross-Platform and Native Windows -- 10. Filters and Convolution -- 11. General Image Transforms -- 12. Image Analysis -- 13. Histograms and Templates -- 14. Contours -- 15. Background Subtraction -- 16. Keypoints and Descriptors -- 17. Tracking -- 18. Camera Models and Calibration -- 19. Projection and Three-Dimensional Vision -- 20. The Basics of Machine Learning in OpenCV -- 21. StatModel: The Standard Model for Learning in OpenCV -- 22. Object Detection -- 23. Future of OpenCV -- A. Planar Subdivisions -- B. opencv_contrib -- C. Calibration Patterns.
520			_a"This book provides a working guide to the C++ Open Source Computer Vision Library (OpenCV) version 3.x and gives a general background on the field of computer vision sufficient to help readers use OpenCV effectively."--Preface.
520			_a"Get started in the rapidly expanding field of computer vision with this practical guide ... this book provides a thorough introduction for developers, academics, roboticists, and hobbyists. You'll learn what it takes to build applications that enable computers to "see" and make decisions based on that data. With over 500 functions that span many areas in vision, OpenCV is used for commercial applications such as security, medical imaging, pattern and face recognition, robotics, and factory product inspection. This book gives you a firm grounding in computer vision and OpenCV for building simple or sophisticated vision applications. Hands-on exercises in each chapter help you apply what you've learned. This volume covers the entire library, in its modern C++ implementation, including machine learning tools for computer vision. Learn OpenCV data types, array types, and array operations. Capture and store still and video images with HighGUI. Transform images to stretch, shrink, warp, remap, and repair. Explore pattern recognition, including face detection. Track objects and motion through the visual field. Reconstruct 3D images from stereo vision. Discover basic and advanced machine learning techniques in OpenCV."--Publisher's website.
650		0	_aComputer vision.
650		0	_aComputer vision _xComputer programs.
650		0	_aC++ (Computer program language)
650		0	_aOpenCV (Computer program language)
650		0	_aImage processing _xDigital techniques.
650		0	_aImage analysis.
650		0	_aOpen source software.
700	1		_aBradski, Gary R., _eauthor.
906			_a7 _bcbc _ccopycat _d2 _encip _f20 _gy-gencatlg
942			_2ddc _cBK
955			_brk07 2017-10-03 z-processor _irk07 2017-10-19 to BCCD
999			_c10290 _d10290