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Other titles in the Lecture Notes in Electrical Engineering series:

Lecture Notes Electrical Engineering #13: Unifying Perspectives in Computational and Robot Vision

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Lecture Notes Electrical Engineering #13: Unifying Perspectives in Computational and Robot Vision Cover

 

Synopses & Reviews

Publisher Comments:

The field of computer vision has developed significantly over the last several years and the application areas span a broad range from medicine to robotics and surveillance. Unifying Perspectives in Computational and Robot Vision provides an overview of the latest research surrounding vision algorithms and their use and evaluation with robotic applications. In robotics, computer vision is mainly seen as another sensory modality and new algorithms are commonly developed for different applications. In the computer vision community, there have been more requirements for benchmarking and comparison of methods but very few are still applied in realistic settings and in real-time which is one of the strongest requirements in robotic applications. Unifying Perspectives in Computational and Robot Vision brings the communities of robot and computer vision to a joint appreciation of the value of systems, where there is a need to consider all aspects from perception to action generation. Based on a workshop "From Features to Actions: Unifying Perspectives in Computational and Robot Vision" that was organized by the editors at the IEEE International Conference on Robotics and Automation (Rome, April 2007), Unifying Perspectives in Computational and Robot Vision will be a valuable resource for readers.

Synopsis:

Assembled in this volume is a collection of some of the state-of-the-art methods that are using computer vision and machine learning techniques as applied in robotic applications. Currently there is a gap between research conducted in the computer vision and robotics communities. This volume discusses contrasting viewpoints of computer vision vs. robotics, and provides current and future challenges discussed from a research perspective.

Synopsis:

Currently there is a gap between the research conducted in computer vision and robotics communities. There are many characteristics in common in computer vision research and vision research in robotics. Despite having these common interests, however, pure computer vision has seen significant theoretical and methodological advances during the last decade which many of the robotics researchers are not fully aware of. On the other hand, the manipulation and control capabilities of robots as well as the range of application areas have developed greatly. In robotics, vision can not be considered an isolated component, but it is instead a part of a system resulting in an action. Thus, in robotics the vision research must include consideration of the control of the system, in other words, the entire perception-action loop. This requires that a holistic system approach is useful and could provide significant advances in this application domain. Assembled here is a collection of some of the state of the art methods that are using computer vision and machine learning techniques and apply them in robotic applications.

Table of Contents

Recent trends in computational and robot vision.- Extracting planar kinematic models using interactive perception.- People detection using multiple sensors on a mobile robot.- Perceiving objects and movements to generate actions on a humanoid robot.- Wald's sequential analysis for time-constrained vision problems.- Pose estimation and feature tracking for robot assisted surgery with medical imaging.- A sliding window filter for incremental SLAM.- Topological and metric robot localization through computer vision techniques.- More vision for SLAM.- Maps, objects and contexts for robots.- Vision-based navigation strategies.- Image-based visual servoing with extra task related constraints in a general framework for senior-based robot systems.

Product Details

ISBN:
9780387755212
Author:
Kyrki, Ville
Publisher:
Springer
Editor:
Kragic, Danica
Author:
Kragic, Danica
Subject:
Computer Vision
Subject:
Intelligence (AI) & Semantics
Subject:
Image processing
Subject:
Computer Imaging, Vision, Pattern Recognition and Graphics
Subject:
Image Processing and Computer Vision
Subject:
Control, Robotics, Mechatronics
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
Artificial Intelligence (incl. Robotics) <P>Demonstrates state of the art in applying computer vision in robotics</P> <P>Discusses contrasting viewpoints of computer vision vs robotics</P> <P>Provides current and future challenges discussed from research
Subject:
Computers-Reference - General
Copyright:
Edition Description:
Book
Series:
Lecture Notes in Electrical Engineering
Series Volume:
8
Publication Date:
20080611
Binding:
HARDCOVER
Language:
English
Illustrations:
Y
Pages:
226
Dimensions:
235 x 155 mm

Related Subjects

Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Computers and Internet » Graphics » Image Processing
Engineering » Communications » Telephony
Engineering » Engineering » General Engineering

Lecture Notes Electrical Engineering #13: Unifying Perspectives in Computational and Robot Vision New Hardcover
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$180.25 In Stock
Product details 226 pages Springer - English 9780387755212 Reviews:
"Synopsis" by , Assembled in this volume is a collection of some of the state-of-the-art methods that are using computer vision and machine learning techniques as applied in robotic applications. Currently there is a gap between research conducted in the computer vision and robotics communities. This volume discusses contrasting viewpoints of computer vision vs. robotics, and provides current and future challenges discussed from a research perspective.
"Synopsis" by , Currently there is a gap between the research conducted in computer vision and robotics communities. There are many characteristics in common in computer vision research and vision research in robotics. Despite having these common interests, however, pure computer vision has seen significant theoretical and methodological advances during the last decade which many of the robotics researchers are not fully aware of. On the other hand, the manipulation and control capabilities of robots as well as the range of application areas have developed greatly. In robotics, vision can not be considered an isolated component, but it is instead a part of a system resulting in an action. Thus, in robotics the vision research must include consideration of the control of the system, in other words, the entire perception-action loop. This requires that a holistic system approach is useful and could provide significant advances in this application domain. Assembled here is a collection of some of the state of the art methods that are using computer vision and machine learning techniques and apply them in robotic applications.
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