Machine Vision for Three-Dimensional Scenes
eBook - PDF

Machine Vision for Three-Dimensional Scenes

  1. 432 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Machine Vision for Three-Dimensional Scenes

About this book

Machine Vision for Three-Dimensional Scenes contains the proceedings of the workshop "Machine Vision - Acquiring and Interpreting the 3D Scene" sponsored by the Center for Computer Aids for Industrial Productivity (CAIP) at Rutgers University and held in April 1989 in New Brunswick, New Jersey. The papers explore the applications of machine vision in image acquisition and 3D scene interpretation and cover topics such as segmentation of multi-sensor images; the placement of sensors to minimize occlusion; and the use of light striping to obtain range data.Comprised of 14 chapters, this book opens with a discussion on 3D object recognition and the problems that arise when dealing with large object databases, along with solutions to these problems. The reader is then introduced to the free-form surface matching problem and object recognition by constrained search. The following chapters address the problem of machine vision inspection, paying particular attention to the use of eye tracking to train a vision system; images of 3D scenes and the attendant problems of image understanding; the problem of object motion; and real-time range mapping. The final chapter assesses the relationship between the developing machine vision technology and the marketplace.This monograph will be of interest to practitioners in the fields of computer science and applied mathematics.

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Yes, you can access Machine Vision for Three-Dimensional Scenes by Herbert Freeman in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Front Cover
  2. Machine Vision for Three-Dimensional Scenes
  3. Copyright Page
  4. Table of Contents
  5. Preface
  6. Contributors
  7. Chapter 1. A Framework for 3D Recognition
  8. Chapter 2. The Free-Form Surface Matching Problem
  9. Chapter 3. Object Recognition by Constrained Search
  10. Chapter 4. The Use of Characteristic-View Classes for 3D Object Recognition
  11. Chapter 5. Interpretation of 3D Medical Scenes
  12. Chapter 6. 3D Motion Estimation
  13. Chapter 7. Project LESTRADE: The Design of a Trainable Machine Vision Inspection System
  14. Chapter 8. Fast 3D Integrated Circuit Inspection
  15. Chapter 9. Segmentation and Analysis of Multi-Sensor Images
  16. Chapter 10. Occlusion-Free Sensor Placement Planning
  17. Chapter 11. The State of the Art in Real-Time Range Mapping — A Panel Discussion
  18. Chapter 12. Generalized and Separable Sobel Operators
  19. Chapter 13. A Fast Lightstripe Rangefinding System with Smart VLSI Sensor
  20. Chapter 14. Machine Vision- Does the Technology Satisfy the Market-place? — A Panel Discussion
  21. Index