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Radu Bogdan Rusu. Acquiring Models of Everyday Activities for Robotic Control in 'Current PhD Research in Pervasive Computing'. Technical Reports - University of Munich, Department of Computer Science, Media Informatics Group, LMU-MI-2005-3, March 2006.
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Abstract
Intelligent sensor equipped environments can be of much greater help if they are capable of recognizing the actions and activities of their users, and inferring their intentions. An intelligent kitchen that recognizes what a person is looking for can highlight the target object. An oven noticing that the cook is on the phone can reduce the heating temperature, in order to avoid the meal getting burnt. In my dissertation research, I investigate the representation of models of everyday activities and study how such models can be learned from sensory data.
BibTeX Entry
@Article{Rusu06Linz,
author = {Radu Bogdan Rusu},
title = {Acquiring Models of Everyday Activities for Robotic Control
in 'Current {PhD} Research in Pervasive Computing'},
editor = {A. Ferscha and M. Langheinrich and A. Schmidt},
journal = {Technical Reports - University of Munich,
Department of Computer Science, Media Informatics Group},
volume = {LMU-MI-2005-3},
year = {2006},
month = {March},
ISSN = {1862-5207},
bib2html_pubtype = {ignore},
bib2html_rescat = {Activity Recognition, Plan-based Robot Control},
bib2html_groups = {IAS},
bib2html_keywords = {Context-aware computing, intentional activity recognition,
probabilistic activity models, sensor data fusion,
artificial intelligence, cognitive robotic systems},
abstract = {Intelligent sensor equipped environments can be of much
greater help if they are capable of recognizing the actions
and activities of their users, and inferring their intentions.
An intelligent kitchen that recognizes what a person is looking
for can highlight the target object. An oven noticing that the
cook is on the phone can reduce the heating temperature, in order
to avoid the meal getting burnt. In my dissertation research,
I investigate the representation of models of everyday activities
and study how such models can be learned from sensory data.},
}
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