Article

Structural descriptions in human-assisted robot visual learning

Authors:

Geert-Jan M. Kruijff,

John D. Kelleher,

Gregor Berginc,

Aleš LeonardisAuthors Info & Claims

HRI '06: Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction

Pages 343 - 344

https://doi.org/10.1145/1121241.1121307

Published: 02 March 2006 Publication History

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Abstract

The paper presents an approach to using structural descriptions, obtained through a human-robot tutoring dialogue, as labels for the visual object models a robot learns. The paper shows how structural descriptions enable relating models for different aspects of one and the same object, and how being able to relate descriptions for visual models and discourse referents enables incremental updating of model descriptions through dialogue (either robot- or human initiated). The approach has been implemented in an integrated architecture for human-assisted robot visual learning.

References

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J. Baldridge and G. J. M. Kruijff. Coupling CCG and hybrid logic dependency semantics. In Proc. ACL 2002, Philadelphia, PA, 2002.

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D. G. Lowe. Distinctive image features from scale-invariant keypoints. In Int. Jnl. Computer Vision, pages 91--110, 2004.

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D. K. Roy. Semiotic schemas: A framework for grounding language in the action and perception. Artificial Intelligence, to appear.

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Cited By

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Liu RGuo YJin RZhang X(2024)A Review of Natural-Language-Instructed Robot Execution SystemsAI10.3390/ai50300485:3(948-989)Online publication date: 26-Jun-2024
https://doi.org/10.3390/ai5030048
Fritz MKruijff GSchiele B(2010)Tutor-based learning of visual categories using different levels of supervisionComputer Vision and Image Understanding10.1016/j.cviu.2009.12.008114:5(564-573)Online publication date: 1-May-2010
https://dl.acm.org/doi/10.1016/j.cviu.2009.12.008
Kruijff GLison PBenjamin TJacobsson HZender HKruijff-Korbayová IHawes N(2010)Situated Dialogue Processing for Human-Robot InteractionCognitive Systems10.1007/978-3-642-11694-0_8(311-364)Online publication date: 2010
https://doi.org/10.1007/978-3-642-11694-0_8
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Index Terms

Structural descriptions in human-assisted robot visual learning
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Scene understanding
    2. Natural language processing

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Information

Published In

HRI '06: Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction

March 2006

376 pages

ISBN:1595932941

DOI:10.1145/1121241

General Chair:
Michael A. Goodrich
Brigham Young University USA
,
Program Chairs:
Alan C. Schultz
Naval Research Laboratory, USA
,
David J. Bruemmer
Idaho National Laboratory, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 March 2006

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Conference

HRI06

Sponsor:

HRI06: International Conference on Human Robot Interaction

March 2 - 3, 2006

Utah, Salt Lake City, USA

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Overall Acceptance Rate 268 of 1,124 submissions, 24%

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Cited By

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Liu RGuo YJin RZhang X(2024)A Review of Natural-Language-Instructed Robot Execution SystemsAI10.3390/ai50300485:3(948-989)Online publication date: 26-Jun-2024
https://doi.org/10.3390/ai5030048
Fritz MKruijff GSchiele B(2010)Tutor-based learning of visual categories using different levels of supervisionComputer Vision and Image Understanding10.1016/j.cviu.2009.12.008114:5(564-573)Online publication date: 1-May-2010
https://dl.acm.org/doi/10.1016/j.cviu.2009.12.008
Kruijff GLison PBenjamin TJacobsson HZender HKruijff-Korbayová IHawes N(2010)Situated Dialogue Processing for Human-Robot InteractionCognitive Systems10.1007/978-3-642-11694-0_8(311-364)Online publication date: 2010
https://doi.org/10.1007/978-3-642-11694-0_8
Skočaj DKristan MVrečko ALeonardis AFritz MStark MSchiele BHongeng SWyatt J(2010)Multi-modal LearningCognitive Systems10.1007/978-3-642-11694-0_7(265-309)Online publication date: 2010
https://doi.org/10.1007/978-3-642-11694-0_7
Kelleher JKruijff G(2006)Incremental generation of spatial referring expressions in situated dialogProceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics10.3115/1220175.1220306(1041-1048)Online publication date: 17-Jul-2006
https://dl.acm.org/doi/10.3115/1220175.1220306
Kruijff GZender HJensfelt PChristensen H(2006)Situated dialogue and understanding spatial organization: Knowing what is where and what you can do thereROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication10.1109/ROMAN.2006.314438(328-333)Online publication date: Sep-2006
https://doi.org/10.1109/ROMAN.2006.314438
Kruijff GKelleher JHawes N(2006)Information fusion for visual reference resolution in dynamic situated dialogueProceedings of the 2006 international tutorial and research conference on Perception and Interactive Technologies10.1007/11768029_12(117-128)Online publication date: 19-Jun-2006
https://dl.acm.org/doi/10.1007/11768029_12

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