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  • © 2014

Concise Computer Vision

An Introduction into Theory and Algorithms

Authors:

  • Presents an accessible general introduction to the essential topics in computer vision

  • Provides classroom-tested programming exercises and review questions at the end of each chapter

  • Includes supporting information on historical context, suggestions for further reading and hints on mathematical subjects under discussion

  • Includes supplementary material: sn.pub/extras

Part of the book series: Undergraduate Topics in Computer Science (UTICS)

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eBook USD 44.99
Price excludes VAT (USA)
  • ISBN: 978-1-4471-6320-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
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  • Tax calculation will be finalised during checkout
Softcover Book USD 59.99
Price excludes VAT (USA)

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Table of contents (10 chapters)

  1. Front Matter

    Pages I-XVIII
  2. Image Data

    • Reinhard Klette
    Pages 1-42
  3. Image Processing

    • Reinhard Klette
    Pages 43-87
  4. Image Analysis

    • Reinhard Klette
    Pages 89-133
  5. Dense Motion Analysis

    • Reinhard Klette
    Pages 135-166
  6. Image Segmentation

    • Reinhard Klette
    Pages 167-214
  7. Cameras, Coordinates, and Calibration

    • Reinhard Klette
    Pages 215-243
  8. 3D Shape Reconstruction

    • Reinhard Klette
    Pages 245-286
  9. Stereo Matching

    • Reinhard Klette
    Pages 287-330
  10. Feature Detection and Tracking

    • Reinhard Klette
    Pages 331-374
  11. Object Detection

    • Reinhard Klette
    Pages 375-413
  12. Back Matter

    Pages 415-429

About this book

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.

Keywords

  • Computer Vision
  • Feature Detection and Tracking
  • Image Processing and Analysis
  • Image Segmentation
  • Object Detection
  • Shape Reconstruction

Authors and Affiliations

  • Computer Science Department, University of Auckland, Auckland, New Zealand

    Reinhard Klette

About the author

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.

Bibliographic Information

  • Book Title: Concise Computer Vision

  • Book Subtitle: An Introduction into Theory and Algorithms

  • Authors: Reinhard Klette

  • Series Title: Undergraduate Topics in Computer Science

  • DOI: https://doi.org/10.1007/978-1-4471-6320-6

  • Publisher: Springer London

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer-Verlag London Ltd., part of Springer Nature 2014

  • Softcover ISBN: 978-1-4471-6319-0

  • eBook ISBN: 978-1-4471-6320-6

  • Series ISSN: 1863-7310

  • Series E-ISSN: 2197-1781

  • Edition Number: 1

  • Number of Pages: XVIII, 429

  • Number of Illustrations: 69 b/w illustrations, 229 illustrations in colour

  • Topics: Computer Vision, Artificial Intelligence

Buying options

eBook USD 44.99
Price excludes VAT (USA)
  • ISBN: 978-1-4471-6320-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 59.99
Price excludes VAT (USA)