neural networks research group
areas
people
projects
demos
publications
software/data
Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting (2008)
Juhyun Lee
and
W. Bradley Knox
and
Peter Stone
"For a mobile robot that interacts with humans such as a home assistant or a tour guide robot, activities such as locating objects, following specific people, and distinguishing among different people are fundamental, yet challenging robotic vision tasks. For complex object recognition and tracking tasks such as person recognition and tracking, we use the method of inter-classifier feedback to track both uniquely identifying characteristics of a person (e.g. face), and more frequently visible, but perhaps less uniquely identifying characteristics (e.g. shirt). The inter-classifier feedback enables merging multiple, heterogeneous sub-classifiers designed to track and associate different characteristics of a person being tracked. These heterogeneous sub-classifiers give feedback to each other by identifying additional online training data for one another, thus improving the performance of the overall tracking system. We implement the tracking system on a Segway base that successfully performed aforementioned activities to a second place finish in the RoboCup
View:
PDF
,
PS
,
HTML
Citation:
Journal of Physical Agents
, 2(2):41-50, July 2008. Special Issue on Human Interaction with Domestic Robots.
Bibtex:
@Article{JOPHA08-lee, title={Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting}, author={Juhyun Lee and W. Bradley Knox and Peter Stone}, volume={2}, journal={Journal of Physical Agents}, number={2}, month={July}, pages={41-50}, note={Special Issue on Human Interaction with Domestic Robots}, url="http://nn.cs.utexas.edu/?JOPHA08-lee", year={2008} }
People
W. Bradley Knox
bradknox [at] mit edu
Juhyun Lee
impjdi [at] gmail com
Peter Stone
pstone [at] cs utexas edu
Areas of Interest
Enabling Technologies
Planning
RoboCup
Robot Vision
Social Agents
Other Areas