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Applying High-Level Understanding to Visual Localisation for Mapping

Taylor, Trevor (2007) Applying High-Level Understanding to Visual Localisation for Mapping. In Mukhopadhyay, Subhas & Sen Gupta, Gourab (Eds.) Autonomous Robots and Agents, Studies in Computational Intelligence. Springer, Berlin Heidelberg, pp. 35-42.

Abstract

Digital cameras are often used on robots these days. One of the common limitations of these cameras is a relatively small field of view. Consequently, the camera is usually tilted downwards to see the floor immediately in front of the robot in order to avoid obstacles. With the camera tilted, vertical edges no longer appear vertical in the image. This feature can however be used to advantage to discriminate amongst straight line edges extracted from the image when searching for landmarks. It might also be used to estimate angles of rotation and distances moved between successive images in order to assist with localisation. Horizontal edges in the real world very rarely appear horizontal in the image due to perspective. By mapping these back to real-world coordinates, it is possible to use the locations of these edges in two successive images to measure rotations or translations of the robot.

Impact and interest:

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ID Code: 9466
Item Type: Book Chapter
Additional Information: For more information about this book please refer to the publisher's website (see link) or contact the author.
Additional URLs:
Keywords: computer vision, monocular camera, camera tilt, perspective, visual localisation
ISBN: 9783540734239
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2007 Springer
Deposited On: 13 Sep 2007
Last Modified: 29 Feb 2012 23:33

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