Computer Vision: Algorithms and Applications

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Springer Science & Business Media, Sep 30, 2010 - Computers - 812 pages
3 Reviews

Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art?

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.

More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques

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
  • Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects
  • Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory
  • Suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book
  • Supplies supplementary course material for students at the associated website,

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.


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User Review - Flag as inappropriate

The book is about everything and nothing -- Jack of all trades and master of none. It can be treated as a list of references. It rather mentions concepts instead of explaining them.


Chapter 2 Image formation
Chapter 3 Image processing
Chapter 4 Feature detection and matching
Chapter 5 Segmentation
Chapter 6 Featurebased alignment
Chapter 7 Structure from motion
Chapter 8 Dense motion estimation
Chapter 9 Image stitching
Chapter 12 3D reconstruction
Chapter 13 Imagebased rendering
Chapter 14 Recognition
Chapter 15 Conclusion
Appendix A Linear algebra and numerical techniques
Appendix B Bayesian modeling and inference
Appendix C Supplementary material

Chapter 10 Computational photography
Chapter 11 Stereo correspondence

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About the author (2010)

Dr. Richard Szeliski has more than 25 years’ experience in computer vision research, most notably at Digital Equipment Corporation and Microsoft Research. This text draws on that experience, as well as on computer vision courses he has taught at the University of Washington and Stanford.

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