Beat-based gesture recognition for non-secure, far-range, or obscured perception scenarios
Graylin Trevor Jay, Patrick Beeson, and Odeste Chadwicke Jenkins. Beat-based gesture recognition for non-secure, far-range, or obscured perception scenarios. In IJCAI Workshop on Space, Time and Ambient Intelligence (STAMI), Barcelona, Spain, July 2011.
Abstract
Gesture recognition is an important communication modality for a variety of human-robot applications, including mobile robotics and ambient intelligence domains. Most gesture recognition systems focus on estimating the position of the arm with respect to the torso of a tracked human. As an alternative, we present a novel approach to gesture recognition that focuses on reliable detection of time-dependent, cyclic “beats” given by a human user. While the expressiveness of “beat-based” gestures is limited, beat-based gesture recognition has several benefits, including reliable 2D gesture detection at far ranges, gesture detection anywhere in the image frame, detection when the human is mostly hidden or obscured, and secure detection via randomly rotated beat patterns that are known only by the user and the perception system. In addition to discussing this complimentary approach to gesture recognition, we also overview a preliminary implementation of beat-based gestures, and demonstrate some initial successes.
BibTeX
@InProceedings{Jay-stami-11,
author = {Graylin Trevor Jay and Patrick Beeson and Odeste
Chadwicke Jenkins},
title = {Beat-based gesture recognition for non-secure,
far-range, or obscured perception scenarios},
booktitle = {IJCAI Workshop on Space, Time and Ambient
Intelligence (STAMI)},
year = 2011,
address = {Barcelona, Spain},
month = {July},
abstract = {Gesture recognition is an important communication
modality for a variety of human-robot applications,
including mobile robotics and ambient intelligence
domains. Most gesture recognition systems focus on
estimating the position of the arm with respect to
the torso of a tracked human. As an alternative, we
present a novel approach to gesture recognition that
focuses on reliable detection of time-dependent,
cyclic ``beats'' given by a human user. While the
expressiveness of ``beat-based'' gestures is
limited, beat-based gesture recognition has several
benefits, including reliable 2D gesture detection at
far ranges, gesture detection anywhere in the image
frame, detection when the human is mostly hidden or
obscured, and secure detection via randomly rotated
beat patterns that are known only by the user and
the perception system. In addition to discussing
this complimentary approach to gesture recognition,
we also overview a preliminary implementation of
beat-based gestures, and demonstrate some initial
successes.},
bib2html_pubtype ={Workshop},
bib2html_rescat ={HRI},
}