BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Learning OpenCV: Computer Vision With the Opencv Library

Learning OpenCV: Computer Vision With the Opencv Library

Learning OpenCV: Computer Vision With the Opencv Library
Stock photo: cover may vary

Learning OpenCV: Computer Vision With the Opencv Library Paperback - 2008 - 1st Edition

by Bradski, Gary/ Kaehler, Adrian

Add to wish list
  • New
  • Paperback

The authors of "OpenCV" explain how to put computer vision to work. They bring readers up to speed with the latest updates in the field and show them how to program with existing free code.

New

Description

Oreilly & Associates Inc, 2008. Paperback. New. 555 pages. 9.25x7.00x1.25 inches.
Ask the seller a question Add to wish list
A$117.32
A$47.50 Delivery to USA
Standard delivery: 7 to 14 days
More delivery options
Ships from Revaluation Books (Devon, United Kingdom)
The BIBLIO Guarantee

Details

  • Title Learning OpenCV: Computer Vision With the Opencv Library
  • Author Bradski, Gary/ Kaehler, Adrian
  • Binding Paperback
  • Edition number 1st
  • Edition 1
  • Condition New
  • Pages 575
  • Volumes 1
  • Language ENG
  • Publisher Oreilly & Associates Inc, Sebastopol, CA, U.S.A
  • Publication date 2008
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index, Table of Contents
  • Bookseller's Inventory # x-0596516134
  • ISBN 9780596516130 / 0596516134
  • Weight 2 lbs (0.91 kg)
  • Dimensions 9.2 x 7 x 1.2 in (23.37 x 17.78 x 3.05 cm)
  • Category Computers - General Information
  • Dewey Decimal Code 006.37
  • Quantity available 2

About Revaluation Books Devon, United Kingdom

Biblio member since 2020

General bookseller of both fiction and non-fiction.

Terms of Sale: 30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from Revaluation Books

Reader reviews for Learning OpenCV: Computer Vision With the Opencv Library

Write a review for this book

There are no reviews for this book yet. Be the first to write a review!

Your review will be anonymous unless you login or create an account first.

Overall rating
Remember: You’re rating the book as a work, not the seller or the condition of the specific copy you purchased!

Important Terms and Guidelines

  • Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
  • Reviews must be at least 140 characters in length.
  • Please do not reveal critical plot elements.
  • This is not a help line. Contact customer support if you need help.
Your review must not include:
  • Obscenities, discriminatory language, or other insulting language not suitable for public domain
  • Advertisements, “spam” content, or references to other products, offers or websites.
  • Email addresses, URLs, phone numbers, physical addresses or other contact information.
  • Overly critical comments about other reviews or reviewers
  • Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
  • Availability, price, or alternative ordering/shipping information

From the publisher

"This library is useful for practitioners, and is an excellent tool for those entering the field: it is a set of computer vision algorithms that work as advertised." -William T. Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology

Learning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to "see" and make decisions based on that data.

Computer vision is everywhere-in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps and Google Earth together, checks the pixels on LCD screens, and makes sure the stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time.

Learning OpenCV will teach any developer or hobbyist to use the framework quickly with the help of hands-on exercises in each chapter. This book includes:
  • A thorough introduction to OpenCV
  • Getting input from cameras
  • Transforming images
  • Segmenting images and shape matching
  • Pattern recognition, including face detection
  • Tracking and motion in 2 and 3 dimensions
  • 3D reconstruction from stereo vision
  • Machine learning algorithms

Getting machines to see is a challenging but entertaining goal. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book you need to get started.

Media reviews

Citations

  • Scitech Book News, 03/01/2009, Page 147

About the author

Dr. Gary Rost Bradski is a consulting professor in the CS department at Stanford University AI Lab where he mentors robotics, machine learning and computer vision research. He is also Senior Scientist at Willow Garage http: //www.willowgarage.com, a recently founded robotics research institute/incubator. He has a BS degree in EECS from U.C. Berkeley and a PhD from Boston University. He has 20 years of industrial experience applying machine learning and computer vision spanning option trading operations at First Union National Bank, to computer vision at Intel Research to machine learning in Intel Manufacturing and several startup companies in between. Gary started the Open Source Computer Vision Library (OpenCV http: //sourceforge.net/projects/​opencvlibrary/ ), the statistical Machine Learning Library (MLL comes with OpenCV), and the Probabilistic Network Library (PNL). OpenCV is used around the world in research, government and commercially. The vision libraries helped develop a notable part of the commercial Intel performance primitives library (IPP http: //tinyurl.com/36ua5s). Gary also organized the vision team for Stanley, the Stanford robot that won the DARPA Grand Challenge autonomous race across the desert for a $2M team prize and helped found the Stanford AI Robotics project at Stanford http: //www.cs.stanford.edu/group/stair/ working with Professor Andrew Ng. Gary has over 50 publications and 13 issued patents with 18 pending. He lives in Palo Alto with his wife and 3 daughters and bikes road or mountains as much as he can.

Dr. Adrian Kaehler is a senior scientist at Applied Minds Corporation. His current research includes topics in machine learning, statistical modeling, computer vision and robotics. Adrian received his Ph.D. in Theoretical Physics from Columbia university in 1998. Adrian has since held positions at Intel Corporation and the Stanford University AI Lab, and was a member of the winning Stanley race team in the DARPA Grand Challenge. He has a variety of published papers and patents in physics, electrical engineering, computer science, and robotics.

Please wait a moment while we load the requested page.

tracking-