000			03092nam a22002777i 4500
020			_a9781491937990
020			_a1491937998
082	0	4	_a006.37 _bKAE
100	1		_aKaehler, Adrian,
245	1	0	_aLearning OpenCV 3 : computer vision in C++ with the OpenCV library _cAdrian Kaehler and Gary Bradski.
250			_aFirst edition, Second release.
260			_aSebastopol, CA : _bO'Reilly Media, _c2017
300			_axxv, 990 pages : _billustrations ;
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
650		0	_aC++ (Computer program language)
650		0	_aOpenCV (Computer program language)
650		0	_aImage processing
650		0	_aImage analysis.
650		0	_aOpen source software.
700	1		_aBradski, Gary R.,
942			_cREF
999			_c45146 _d45146