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Concise Computer Vision: An Introduction into Theory and Algorithms (Undergraduate Topics in Computer Science) [Englisch] [Taschenbuch]

Reinhard Klette

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Kurzbeschreibung

31. Januar 2014 1447163192 978-1447163190 2014
This textbook provides an accessible general introduction to the essential topics in computer vision. Classroom-tested programming exercises and review questions are also supplied at the end of each chapter. Features: provides an introduction to the basic notation and mathematical concepts for describing an image and the key concepts for mapping an image into an image; explains the topologic and geometric basics for analysing image regions and distributions of image values and discusses identifying patterns in an image; introduces optic flow for representing dense motion and various topics in sparse motion analysis; describes special approaches for image binarization and segmentation of still images or video frames; examines the basic components of a computer vision system; reviews different techniques for vision-based 3D shape reconstruction; includes a discussion of stereo matchers and the phase-congruency model for image features; presents an introduction into classification and learning.

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Many textbooks on computer vision can be unwieldy and intimidating in their coverage of this extensive discipline. This textbook addresses the need for a concise overview of the fundamentals of this field.

Concise Computer Vision provides an accessible general introduction to the essential topics in computer vision, highlighting the role of important algorithms and mathematical concepts. Classroom-tested programming exercises and review questions are also supplied at the end of each chapter.

Topics and features:

  • Provides an introduction to the basic notation and mathematical concepts for describing an image, and the key concepts for mapping an image into an image
  • Explains the topologic and geometric basics for analysing image regions and distributions of image values, and discusses identifying patterns in an image
  • Introduces optic flow for representing dense motion, and such topics in sparse motion analysis as keypoint detection and descriptor definition, and feature tracking using the Kalman filter
  • Describes special approaches for image binarization and segmentation of still images or video frames
  • Examines the three basic components of a computer vision system, namely camera geometry and photometry, coordinate systems, and camera calibration
  • Reviews different techniques for vision-based 3D shape reconstruction, including the use of structured lighting, stereo vision, and shading-based shape understanding
  • Includes a discussion of stereo matchers, and the phase-congruency model for image features
  • Presents an introduction into classification and learning, with a detailed description of basic AdaBoost and the use of random forests

This concise and easy to read textbook/reference is ideal for an introductory course at third- or fourth-year level in an undergraduate computer science or engineering programme.

Über den Autor und weitere Mitwirkende

Dr. Reinhard Klette, FRSNZ, is a Professor at the Tamaki Innovation Campus of The University of Auckland, New Zealand. His numerous other publications include the Springer title Euclidean Shortest Paths: Exact or Approximate Algorithms.

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Amazon.com: 4.8 von 5 Sternen  4 Rezensionen
2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen probably the only textbook in the market for computer vision 1. August 2014
Von Turtleman - Veröffentlicht auf Amazon.com
Format:Taschenbuch|Verifizierter Kauf
I took a computer vision class using Szeliski's book,
I was NOT satisfied to the book, so I searched around to find another textbook for learning & reference.
There are some other books in computer vision.

Szeliski: a literature review, NOT a textbook.
Forsyth & Ponce: a famous mess
Prince: title says "computer vision", but it is image processing
Davies: contains both image processing and computer vision, but more toward image processing
Shapiro: so outdated that it does not fit into courses

Finally, I found this book.
This is probably the only textbook available in the market.
The contents are all computer vision topics.
The explanation is very clear in most parts.
Excellent book for learning & reference.
1 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Clear and concise! Great book! 23. Juni 2014
Von Jona - Veröffentlicht auf Amazon.com
Format:Taschenbuch|Verifizierter Kauf
It is a great book on a difficult topic. It covers all the main topics an undergrad course in vision would cover. Provides insight and detailed descriptions of classical and modern methods. I really liked the detailed overview on Viola's method, and a great explanation on Adaboost.
1 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Succinct Exposition of Computer Vision 9. April 2014
Von Shanmuganathan Raman - Veröffentlicht auf Amazon.com
Format:Kindle Edition
I have been teaching computer vision for the past 2 years. There was definitely a dire need for an undergraduate textbook for computer vision. Existing books are more research oriented and not that suitable for classroom use. This book has contents which are succinctly explained and the breadth of topics covered is amazing. This book would best serve the purpose for a first course in computer vision. The important feature I liked about this book is the coverage of state-of-the-art algorithms in computer vision without compromising on the lucidity. I reckon this book would be adopted for various computer vision courses in near future. I also plan to adopt this book for my next offering of computer vision.
1 von 2 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Exciting and easy to understand 17. März 2014
Von Wohlfeil - Veröffentlicht auf Amazon.com
Format:Taschenbuch
This book is a wonderful introduction to the basic topics of computer vision and image processing. Many eye catching images and well drawn figures make it exciting and easy to understand the theory behind many important topics in this field.
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