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Representing actions with Kernels
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.
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: 0000-0003-2965-2953
2011 (English)In: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011, 2028-2035 p.Conference paper, Published paper (Refereed)
Abstract [en]

A long standing research goal is to create robots capable of interacting with humans in dynamic environments.To realise this a robot needs to understand and interpret the underlying meaning and intentions of a human action through a model of its sensory data. The visual domain provides a rich description of the environment and data is readily available in most system through inexpensive cameras. However, such data is very high-dimensional and extremely redundant making modeling challenging.Recently there has been a significant interest in semantic modeling from visual stimuli. Even though results are encouraging available methods are unable to perform robustly in realworld scenarios.In this work we present a system for action modeling from visual data by proposing a new and principled interpretation for representing semantic information. The representation is integrated with a real-time segmentation. The method is robust and flexible making it applicable for modeling in a realistic interaction scenario which demands handling noisy observations and require real-time performance. We provide extensive evaluation and show significant improvements compared to the state-of-the-art.

Place, publisher, year, edition, pages
2011. 2028-2035 p.
Series
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-50663DOI: 10.1109/IROS.2011.6094567ISI: 000297477502058Scopus ID: 2-s2.0-84455207416ISBN: 978-1-61284-454-1 (print)OAI: oai:DiVA.org:kth-50663DiVA: diva2:462369
Conference
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems September 25-30, 2011. San Francisco, CA, USA
Note
QC 20111207Available from: 2011-12-07 Created: 2011-12-07 Last updated: 2012-04-03Bibliographically approved

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Kragic, Danica

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  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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Output format
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