Overview
- Presents state-of-the-art techniques, featuring new material on deep learning and deep neural networks
- Structured to support active curricula and project-oriented courses
- Provides, exercises and additional readings, as well as supplementary material
Part of the book series: Texts in Computer Science (TCS)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (15 chapters)
-
Front Matter
-
Back Matter
Keywords
About this book
Computer Vision: Algorithms and Applications 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.
Topics and features:
- 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
Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
Authors and Affiliations
About the author
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. He was awarded the IEEE Computer Society PAMI Distinguished Researcher Award in 2017 and is an IEEE and ACM Fellow.
Bibliographic Information
Book Title: Computer Vision
Book Subtitle: Algorithms and Applications
Authors: Richard Szeliski
Series Title: Texts in Computer Science
DOI: https://doi.org/10.1007/978-3-030-34372-9
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-34371-2Published: 05 January 2022
Softcover ISBN: 978-3-030-34374-3Published: 06 January 2023
eBook ISBN: 978-3-030-34372-9Published: 03 January 2022
Series ISSN: 1868-0941
Series E-ISSN: 1868-095X
Edition Number: 2
Number of Pages: XXII, 925
Number of Illustrations: 374 b/w illustrations, 144 illustrations in colour
Topics: Image Processing and Computer Vision, Computer Imaging, Vision, Pattern Recognition and Graphics, Machine Learning, Signal, Image and Speech Processing, Materials Science, general