Computer Vision: Algorithms and Applications

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  coursesIncorporates totally new material on deep learning and  applications such as mobile computational photography, autonomous  navigation, and augmented realityPresents 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.