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020 _a9781848829350
_9978-1-84882-935-0
024 7 _a10.1007/978-1-84882-935-0
_2doi
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072 7 _aUYQV
_2bicssc
072 7 _aCOM012000
_2bisacsh
072 7 _aUYQV
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082 0 4 _a006.37
_223
100 1 _aSzeliski, Richard.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_931916
245 1 0 _aComputer Vision
_h[electronic resource] :
_bAlgorithms and Applications /
_cby Richard Szeliski.
250 _a1st ed. 2011.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2011.
300 _aXX, 812 p. 574 illus., 560 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTexts in Computer Science,
_x1868-095X
505 0 _aIntroduction -- Image Formation -- Image Processing -- Feature Detection and Matching -- Segmentation -- Feature-based Alignment -- Structure from Motion -- Dense Motion Estimation -- Image Stitching -- Computational Photography -- Stereo Correspondence -- 3D Reconstruction -- Image-based Rendering -- Recognition.
520 _aHumans 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, http://szeliski.org/Book/ 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. 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.
650 0 _aComputer vision.
_931917
650 1 4 _aComputer Vision.
_931918
710 2 _aSpringerLink (Online service)
_931919
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9781848829466
776 0 8 _iPrinted edition:
_z9781848829343
830 0 _aTexts in Computer Science,
_x1868-095X
_931920
856 4 0 _uhttps://doi.org/10.1007/978-1-84882-935-0
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