03881nam a22004457i 450000100060000000300090000600500170001500800410003201000170007302000180009002000150010803500240012303701090014704000990025604200140035505000220036908200110039110000300040224501050043224600110053724600510054825000190059926000890061830000450070750400670075250508000081952002330161952012580185252600080311065000210311865000400313965000360317965000390321565000420325465000200329665000260331665000220334270000310336485200400339544229BD-DhAAL20250505152107.0250318p20212016cc a     b    001 0 eng d  a  2016439939  a9781491937990  a1491937998  a(OCoLC)ocn968936315  bOreilly & Associates Inc, C/O Ingram Pub Services 1 Ingram Blvd, LA Vergne, TN, USA, 37086nSAN 631-8673  aSXPbengcSXPerdadSXPdJRZdOQXdOCLCFdYDXdOCLCQdCLUdUNBCAdBDXdOCLdSFRdDLCdBD-DhAAL  alccopycat00aTA1634b.K34 201704a006.371 aKaehler, Adrian,eauthor.10aLearning OpenCV 3 :bcomputer vision in C++ with the OpenCV library /cAdrian Kaehler, Gary Bradski.30aOpenCV30aComputer vision in C++ with the OpenCV library  aFirst edition.  aBeijing ;aBoston ;aSebastopol, CA :bO'Reilly Media,c2016 [fourth released 2021].  axxv, 994 pages :billustrations ;c24 cm  aIncludes bibliographical references (pages 949-965) and index.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.  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.  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.  aCSE 0aComputer vision. 0aComputer visionxComputer programs. 0aC++ (Computer program language) 0aOpenCV (Computer program language) 0aImage processingxDigital techniques. 0aImage analysis. 0aOpen source software. 0aComputer science.1 aBradski, Gary R.,eauthor.  aAyesha Abed LibrarycGeneral Stacks