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Improved mapping and image segmentation by using semantic information to link aerial images and ground-level information
Örebro University, School of Science and Technology. (AASS)
Department of Computing and Informatics, University of Lincoln, Lincoln, UK.
Örebro University, School of Science and Technology. (Learning Systems Lab)ORCID iD: 0000-0003-0217-9326
2008 (English)In: Recent Progress in Robotics: Viable Robotic Service to Human, Berlin, Germany: Springer, 2008, p. 157-169Conference paper, Published paper (Other academic)
Abstract [en]

This paper investigates the use of semantic information to link ground-level occupancy maps and aerial images. A ground-level semantic map is obtained by a mobile robot equipped with an omnidirectional camera, differential GPS and a laser range finder. The mobile robot uses a virtual sensor for building detection (based on omnidirectional images) to compute the ground-level semantic map, which indicates the probability of the cells being occupied by the wall of a building. These wall estimates from a ground perspective are then matched with edges detected in an aerial image. The result is used to direct a region- and boundary-based segmentation algorithm for building detection in the aerial image. This approach addresses two difficulties simultaneously: 1) the range limitation of mobile robot sensors and 2) the difficulty of detecting buildings in monocular aerial images. With the suggested method building outlines can be detected faster than the mobile robot can explore the area by itself, giving the robot an ability to “see” around corners. At the same time, the approach can compensate for the absence of elevation data in segmentation of aerial images. Our experiments demonstrate that ground-level semantic information (wall estimates) allows to focus the segmentation of the aerial image to find buildings and produce a ground-level semantic map that covers a larger area than can be built using the onboard sensors.

Place, publisher, year, edition, pages
Berlin, Germany: Springer, 2008. p. 157-169
Series
Lecture Notes in Control and Information Sciences, ISSN 0170-8643 ; 370
Keywords [en]
Semantic Mapping, Aerial Images, Mobile Robotics
National Category
Engineering and Technology Computer and Information Sciences
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-3297DOI: 10.1007/978-3-540-76729-9_13ISI: 000252925100011Scopus ID: 2-s2.0-36749046368ISBN: 978-3-540-76728-2 (print)OAI: oai:DiVA.org:oru-3297DiVA, id: diva2:137594
Conference
13th International Conference on Advanced Robotics, Jeju Isl, South Korea
Available from: 2008-11-28 Created: 2008-11-28 Last updated: 2018-06-13Bibliographically approved

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Improved mapping and image segmentation by using semantic information to link aerial images and ground-level information(253 kB)48 downloads
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Persson, MartinLilienthal, Achim J.

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