Concise Computer Vision

An Introduction into Theory and Algorithms
2014
ISBN: 978-1-4471-6319-0
Verlag: Springer

Buch, Englisch, 429 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 7545 g

Reihe: Undergraduate Topics in Computer Science

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.

Zielgruppe

Upper undergraduate

Autoren/Hrsg.

Klette, Reinhard

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision

Inhaltsverzeichnis

1: Image Data.- 2: Image Processing.- 3: Image Analysis.- 4: Dense Motion Analysis.- 5: Image Segmentation.- 6: Cameras, Coordinates and Calibration.- 7: 3D Shape Reconstruction.- 8: Stereo Matching.- 9: Feature Detection and Tracking.- 10: Object Detection.

Über Autor(innen)

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.