"This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data. With minimal prerequisites, the book starts from the basics of probability and model fitting and works up to real examples that the reader can implement and modify to build useful vision systems. Primarily meant for advanced undergraduate and graduate students, the detailed methodological presentation will also be useful for practitioners of computer vision. [bullet] Covers cutting-edge techniques, including graph cuts, machine learning and multiple view geometry [bullet] A unified approach shows the common basis for solutions of important computer vision problems, such as camera calibration, face recognition and object tracking [bullet] More than 70 algorithms are described in sufficient detail to implement [bullet] More than 350 full-color illustrations amplify the text [bullet] The treatment is self-contained, including all of the background mathematics [bullet] Additional resources at www.computervisionmodels.com"--
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Dr Simon J. D. Prince is a faculty member in the Department of Computer Science at University College London. He has taught courses on machine vision, image processing and advanced mathematical methods. He has a diverse background in biological and computing sciences and has published papers across the fields of computer vision, biometrics, psychology, physiology, medical imaging, computer graphics and HCI.
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Da: BooksRun, Philadelphia, PA, U.S.A.
Hardcover. Condizione: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Codice articolo 1107011795-11-1
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Da: Goodwill Books, Hillsboro, OR, U.S.A.
Condizione: good. Signs of wear and consistent use. Codice articolo GICWV.1107011795.G
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Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.
Hardcover. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. Codice articolo G1107011795I3N00
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Da: Books From California, Simi Valley, CA, U.S.A.
hardcover. Condizione: Very Good. Codice articolo mon0004193481
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Da: Better World Books Ltd, Dunfermline, Regno Unito
Condizione: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. Codice articolo 18522864-6
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Da: Anybook.com, Lincoln, Regno Unito
Condizione: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1500grams, ISBN:9781107011793. Codice articolo 3973665
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Da: Moe's Books, Berkeley, CA, U.S.A.
Hard cover. Condizione: Good. No jacket. Cover is worn and rubbed, not affecting legibility of text. Sticker from previous seller on back cover, obscuring some text and affecting legibility. Spine is shaken and cracked, but binding is secure. Inside is clean and unmarked. Codice articolo 1140945
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 15993114-n
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Da: DeckleEdge LLC, Albuquerque, NM, U.S.A.
hardcover. Condizione: new. Codice articolo Shelfdream1107011795
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 15993114
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