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  • © 2022

Computer Vision

Algorithms and Applications

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  • 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)

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eBook
USD 69.99
Price excludes VAT (USA)
  • ISBN: 978-3-030-34372-9
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Hardcover Book
USD 89.95
Price excludes VAT (USA)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-xxii
  2. Introduction

    • Richard Szeliski
    Pages 1-26
  3. Image Formation

    • Richard Szeliski
    Pages 27-83
  4. Image Processing

    • Richard Szeliski
    Pages 85-151
  5. Model Fitting and Optimization

    • Richard Szeliski
    Pages 153-186
  6. Deep Learning

    • Richard Szeliski
    Pages 187-271
  7. Recognition

    • Richard Szeliski
    Pages 273-331
  8. Feature Detection and Matching

    • Richard Szeliski
    Pages 333-399
  9. Image Alignment and Stitching

    • Richard Szeliski
    Pages 401-441
  10. Motion Estimation

    • Richard Szeliski
    Pages 443-482
  11. Computational Photography

    • Richard Szeliski
    Pages 483-542
  12. Structure from motion and SLAM

    • Richard Szeliski
    Pages 543-594
  13. Depth Estimation

    • Richard Szeliski
    Pages 595-638
  14. 3D Reconstruction

    • Richard Szeliski
    Pages 639-680
  15. Image-Based rendering

    • Richard Szeliski
    Pages 681-722
  16. Conclusion

    • Richard Szeliski
    Pages 723-725
  17. Back Matter

    Pages 727-925

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.

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.

Keywords

  • Computer Vision
  • Image Processing
  • Deep Learning
  • 3D Reconstruction
  • Feature Detection and Matching
  • Image Segmentation
  • Structure from Motion
  • Motion Estimation
  • Image Stitching
  • Computational Photography
  • Image-Based Rendering
  • Scene Recognition

Authors and Affiliations

  • University of Washington, Seattle, USA

    Richard Szeliski

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

Buying options

eBook
USD 69.99
Price excludes VAT (USA)
  • ISBN: 978-3-030-34372-9
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Hardcover Book
USD 89.95
Price excludes VAT (USA)