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Computer Vision: Algorithms and Applications, Second Edition
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  • Title: Computer Vision: Algorithms and Applications
  • Author(s) Richard Szeliski
  • Publisher: Springer; 2nd Edition (January 5, 2022); eBook (Final Draft, September 30, 2021)
  • Permission: "This electronic draft is for non-commercial personal use only, and may not be posted or re-distributed in any form."
  • Hardcover: 947 pages
  • eBook: PDF (1232 pages, 38.8 MB)
  • Language: English
  • ISBN-10: 3030343715
  • ISBN-13: 978-3030343712
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Book Description

This book explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.

More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.

  • Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses
  • Incorporates totally new material on Deep Learning and applications such as mobile computational photography, autonomous navigation, and augmented reality
  • Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects
  • Includes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decade
  • Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and software
About the Authors
  • Dr. Richard Szeliski has more than 40 years' experience in computer vision research, most recently at Facebook and Microsoft Research, where he led the Computational Photography and Interactive Visual Media groups. He is currently an Affiliate Professor at the University of Washington where he co-developed (with Steve Seitz) the widely adopted computer vision curriculum on which this book is based.
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