Semantic Networks for Understanding Scenes (Advances in Computer Vision and Machine Intelligence)

Sagerer, Gerhard, Niemann, Heinrich

ISBN 10: 0306457040 / ISBN 13: 9780306457043

Published by Springer, 1997

About this Item

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Seller Inventory # ERICA77303064570406

Bibliographic Details

• Title: Semantic Networks for Understanding Scenes (Advances in Computer Vision and Machine Intelligence)
• Publisher: Springer
• Publication Date: 1997
• Language: English
• ISBN 10: 0306457040
• ISBN 13: 9780306457043
• Binding: Hardcover
• Condition: Like New
• Book Type: book

About this title

Synopsis

Figure 1.1. An outdoor scene "A bus is passing three cars which are parking between trees at the side of the road. Houses having two storeys are lined up at the street. 3 4 Introduction Figure 1.2. An assembly scene There seems to be a small open place between the group of houses in the foreground and the store in the background". In such or a similar way the content of the natural scene shown above can be described. It is quite easy to give such a short description. The problem is somewhat more complex for the second image. First of all, it can be stated that the image does not show an everyday scene. It appears as a kind of man made surrounding. But everyone can accept the following statements about this image: 1. The image shows a snapshot of an assembly line. 2. The robot in front is screwing. 3. There is no person in the working area of the robots. 4. All objects on the conveyor belt are worked on by robots. There are no free objects on the belt.

Synopsis

The explosion in the use of digital imaging in recent years has made it necessary to develop computer languages that can efficiently translate photographic images into their digital analogues. This state-of-the-science guide presents the technical problems that need to be overcome in the development of this technology. The text proceeds from a review of the standard models and system architectures in use today to new systems under investigation. It contains chapters covering: segmentation, knowledge, representation, languages, criteria for judgment, search and control algorithms, explanation in a semantic network applications in medical and industrial contexts, as well as those involved in speech understanding.