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Combining Top-down Spatial Reasoning and Bottom-up Object Class Recognition for Scene Understanding
University of Birmingham.
University of Birmingham.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-0448-3786
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2014 (English)In: Proc. of 2014 IEEE/RSJ International Conference on IntelligentRobots and Systems 2014, IEEE conference proceedings, 2014, 2910-2915 p.Conference paper, Published paper (Refereed)
Abstract [en]

Many robot perception systems are built to only consider intrinsic object features to recognise the class of an object. By integrating both top-down spatial relational reasoning and bottom-up object class recognition the overall performance of a perception system can be improved. In this paper we present a unified framework that combines a 3D object class recognition system with learned, spatial models of object relations. In robot experiments we show that our combined approach improves the classification results on real world office desks compared to pure bottom-up perception. Hence, by using spatial knowledge during object class recognition perception becomes more efficient and robust and robots can understand scenes more effectively.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2014. 2910-2915 p.
Keyword [en]
Spatial Relations, Robotics, Learning
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-156599DOI: 10.1109/IROS.2014.6942963Scopus ID: 2-s2.0-84911478657OAI: oai:DiVA.org:kth-156599DiVA: diva2:767263
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems, 14-18 Sept. 2014, Chicago, IL, USA
Projects
StrandsEuropean Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No 600623
Funder
EU, FP7, Seventh Framework Programme
Note

QC 20141205

Available from: 2014-12-01 Created: 2014-12-01 Last updated: 2016-12-01Bibliographically approved

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fulltext(3768 kB)222 downloads
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Jensfelt, Patric

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Alberti, MarinaThippur, AkshayaFolkesson, JohnJensfelt, Patric
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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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