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Object Localization using Bearing Only Visual Detection
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0002-1170-7162
2008 (English)In: Intelligent Autonomous Systems 10, IAS 2008AS-10: INTELLIGENT AUTONOMOUS SYSTEMS 10 / [ed] Burgard W; Dillmann R; Plagemann C; Vahrenkamp N, AMSTERDAM: I O S PRESS , 2008, 254-263 p.Conference paper, Published paper (Refereed)
Abstract [en]

This work demonstrates how an autonomous robotic platform can use intrinsically noisy, coarse-scale visual methods lacking range information to produce good estimates of the location of objects, by using a map-space representation for weighting together multiple observations from different vantage points. As the robot moves through the environment it acquires visual images which are processed by means of a fast but noisy visual detection algorithm that gives bearing only information. The results from the detection are projected from image space into map space, where data from multiple viewpoints can intrinsically combine to yield an increasingly accurate picture of the location of objects. This method has been implemented and shown to work for object localization on a real robot. It has also been tested extensively in simulation, with systematically varied false positive and false negative detection rates. The results demonstrate that this is a viable method for object localization, even under a wide range of sensor uncertainties.

Place, publisher, year, edition, pages
AMSTERDAM: I O S PRESS , 2008. 254-263 p.
Keyword [en]
Accumulator Grid, Object Detection, Object Localization
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-29673DOI: 10.3233/978-1-58603-887-8-254ISI: 000279575000030Scopus ID: 2-s2.0-84871745506ISBN: 978-1-58603-887-8 (print)OAI: oai:DiVA.org:kth-29673DiVA: diva2:398650
Conference
10th International Conference on Intelligent Autonomous Systems, IAS 2008; Baden-Baden; Germany; 23 July 2008 through 25 July 2008
Funder
EU, European Research Council, CoSySwedish Research Council, 621-2006-4520
Note

QC 20150713

Available from: 2011-02-18 Created: 2011-02-11 Last updated: 2015-07-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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