Advances in Computer Vision and Pattern Recognition

Decision Forests for Computer Vision and Medical Image Analysis

Editors: Criminisi, Antonio, Shotton, J (Eds.)

  • Introduces a flexible decision forest model capable of addressing a large and diverse set of image and video analysis tasks, covering both theoretical foundations and practical implementation
  • Includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website
  • Provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner
see more benefits

Buy this book

eBook n/a
  • ISBN 978-1-4471-4929-3
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
Hardcover n/a
  • ISBN 978-1-4471-4928-6
  • Free shipping for individuals worldwide
Softcover n/a
  • ISBN 978-1-4471-6962-8
  • Free shipping for individuals worldwide
About this book

This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.

Reviews

From the reviews:

“This book is a comprehensive presentation of the theory and use of decision forests in a wide range of applications, centered on computer vision and medical imaging. The book is strikingly well integrated. … This is an excellent volume on the concept, theory, and application of decision forests. … I highly recommend it to those currently working in the field, as well as researchers desiring an introduction to the application of random forests for imaging applications.” (Creed Jones, Computing Reviews, March, 2014)


Table of contents (23 chapters)

  • Overview and Scope

    Criminisi, A. (et al.)

    Pages 1-2

  • Notation and Terminology

    Criminisi, A. (et al.)

    Pages 3-4

  • Introduction: The Abstract Forest Model

    Criminisi, A. (et al.)

    Pages 7-23

  • Classification Forests

    Criminisi, A. (et al.)

    Pages 25-45

  • Regression Forests

    Criminisi, A. (et al.)

    Pages 47-58

Buy this book

eBook n/a
  • ISBN 978-1-4471-4929-3
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
Hardcover n/a
  • ISBN 978-1-4471-4928-6
  • Free shipping for individuals worldwide
Softcover n/a
  • ISBN 978-1-4471-6962-8
  • Free shipping for individuals worldwide
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Decision Forests for Computer Vision and Medical Image Analysis
Editors
  • Antonio Criminisi
  • J Shotton
Series Title
Advances in Computer Vision and Pattern Recognition
Copyright
2013
Publisher
Springer-Verlag London
Copyright Holder
Springer-Verlag London
eBook ISBN
978-1-4471-4929-3
DOI
10.1007/978-1-4471-4929-3
Hardcover ISBN
978-1-4471-4928-6
Softcover ISBN
978-1-4471-6962-8
Series ISSN
2191-6586
Edition Number
1
Number of Pages
XIX, 368
Topics