Generating Object Hypotheses in Natural Scenes through Human-Robot Interaction
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 (Refereed)
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.
, IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
Cognitive Human-Robot Interaction, Computer Vision
IdentifiersURN: urn:nbn:se:kth:diva-43451DOI: 10.1109/IROS.2011.6048162ISI: 000297477501027ScopusID: 2-s2.0-84455201679ISBN: 978-1-61284-454-1OAI: oai:DiVA.org:kth-43451DiVA: diva2:448466
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, San Francisco
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