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Cambridge University Press - Computer Vision Textbook

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Description

Explore the fundamentals of computer vision through this modern treatment by Cambridge University Press. This book focuses on learning and inference in probabilistic models as a unifying theme. It provides a clear path for understanding how to use training data to learn relationships between observed image data and world aspects like object class or 3D structure. Designed with minimal prerequisites, the text begins with the basics of probability and model fitting. It progresses toward real-world examples that readers can implement and modify to build useful vision systems. This approach helps you exploit learned relationships to make new inferences about the world from fresh image data, making it a practical resource for students and professionals in computing and graphics.

Key Features

This Cambridge University Press book focuses on learning and inference in probabilistic models as a unifying theme.

Learn to use training data to estimate 3D structure and object class from observed image data.

The text starts from the basics of probability and model fitting to accommodate readers with minimal prerequisites.

Includes real examples that readers can implement and modify to build useful vision systems.

Provides methods to exploit learned relationships to make new inferences from new image data.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
30 August 2012
Listed Since
06 October 2011

Barcode

No barcode data available

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