Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
  • rtf
Generating Object Hypotheses in Natural Scenes through Human-Robot Interaction
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), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0003-0579-3372
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.ORCID iD: 0000-0003-2965-2953
2011 (English)In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS / [ed] Amato, Nancy M., San Francisco: IEEE , 2011, 827-833 p.Conference paper, Published paper (Refereed)
Abstract [en]

We propose a method for interactive modeling ofobjects and object relations based on real-time segmentation ofvideo sequences. In interaction with a human, the robot canperform multi-object segmentation through principled model-ing of physical constraints. The key contribution is an efficientmulti-labeling framework, that allows object modeling anddisambiguation in natural scenes. Object modeling and labelingis done in a real-time, to which hypotheses and constraintsdenoting relations between objects can be added incrementally.Through instructions such as key presses or spoken words, ascene can be segmented in regions corresponding to multiplephysical objects. The approach solves some of the difficultproblems related to disambiguation of objects merged due totheir direct physical contact. Results show that even a limited setof simple interactions with a human operator can substantiallyimprove segmentation results.

Place, publisher, year, edition, pages
San Francisco: IEEE , 2011. 827-833 p.
Series
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
Keyword [en]
Cognitive Human-Robot Interaction, Computer Vision
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-43451DOI: 10.1109/IROS.2011.6048162ISI: 000297477501027Scopus ID: 2-s2.0-84455201679ISBN: 978-1-61284-454-1 (print)OAI: oai:DiVA.org:kth-43451DiVA: diva2:448466
Conference
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, San Francisco
Note
© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. QC 20111102Available from: 2011-11-02 Created: 2011-10-17 Last updated: 2012-04-03Bibliographically approved

Open Access in DiVA

iros2011bergstrom.pdf(1714 kB)460 downloads
File information
File name FULLTEXT01.pdfFile size 1714 kBChecksum SHA-512
ace3e3531baf7cc804b0e1723c5ec61cc40b19c76614fbdbfe7ac88e3a16a8a3226c1d2be5a2cd60a9fb1322b1a90c870c24f267f117a6ba2766e45c866dc90c
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopusPublished version

Search in DiVA

By author/editor
Bergström, NiklasBjörkman, MårtenKragic, Danica
By organisation
Computer Vision and Active Perception, CVAPCentre for Autonomous Systems, CAS
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 460 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 89 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
  • rtf