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Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library

Description: Get started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, 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

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Location: Gloucester

End Time: 2024-11-10T12:44:42.000Z

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Learning OpenCV 3: Computer Vision in C++ with the OpenCV LibraryLearning OpenCV 3: Computer Vision in C++ with the OpenCV Library

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EAN: 9781491937990

UPC: 9781491937990

ISBN: 9781491937990

MPN: N/A

Book Title: Learning OpenCV 3: Computer Vision in C++ with the

Item Length: 23.6 cm

Item Height: 230 mm

Item Width: 183 mm

Author: Adrian Kaehler, Gary Bradski

Publication Name: Learning Opencv 3

Format: Paperback

Language: English

Publisher: O'reilly Media, INC International Concepts USA

Subject: Computer Science

Publication Year: 2017

Type: Textbook

Item Weight: 1638 g

Number of Pages: 1024 Pages

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