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Computer Vision: Algorithms and Applications (Texts in Computer Science)

Amazon.com Price:  $62.28 (as of 06/04/2019 21:41 PST- Details)

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Description

Computer Vision: Algorithms and Applications explores the variety of techniques recurrently 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 the use of statistical models and solved the use of rigorous engineering techniques.

Topics and features: structured to make stronger active curricula and project-oriented courses, with tips in the Introduction for the use of the book in various customized courses; presents exercises at the end of each and every chapter with a heavy emphasis on testing algorithms and containing a large number of 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 and every chapter, including the recent research in each and every sub-field, along with a full Bibliography at the end of the book; supplies supplementary course material for students at the associated web page, http://szeliski.org/Book/.

Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook specializes in 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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