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Computer vision

by Simon J. D Prince | 18 June 2012
Hardback
Category: Computer Science
Synopsis
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. Covers cutting-edge techniques, including graph cuts, machine learning and multiple view geometry A unified approach shows the common basis for solutions of important computer vision problems, such as camera calibration, face recognition and object tracking More than 70 algorithms are described in sufficient detail to implement More than 350 full-color illustrations amplify the text The treatment is self-contained, including all of the background mathematics Additional resources at www.computervisionmodels.com
€93.79
281 Reward Points
In stock online
Delivery 5-7 Days
Eligible for free delivery

Any purchases for more than €10 are eligible for free delivery anywhere in the UK or Ireland!

Synopsis
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. Covers cutting-edge techniques, including graph cuts, machine learning and multiple view geometry A unified approach shows the common basis for solutions of important computer vision problems, such as camera calibration, face recognition and object tracking More than 70 algorithms are described in sufficient detail to implement More than 350 full-color illustrations amplify the text The treatment is self-contained, including all of the background mathematics Additional resources at www.computervisionmodels.com
Quantity
Quantity
€93.79
281 Reward Points
In stock online
Delivery 5-7 Days
Eligible for free delivery

Any purchases for more than €10 are eligible for free delivery anywhere in the UK or Ireland!

Quantity
Quantity

Product Details

ISBN - 9781107011793
Format - Hardback
Publisher -
Published - 18/06/2012
Categories - All, Books, Business Computers, Computers, Computer Science
No. of Pages - 580
Weight - 1400
Edition -
Series - - Not Available
Page Size - 27
Language - en-US
Readership Age - Not Available
Table of Contents - Not Available

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