Replacing ‘Wave to Engage’ with ‘Intent to Interact’

Schwarz, J., Marais, C., Leyvand, T., Hudson, S., Mankoff, J. Combining Body Pose, Gaze and Motion to Determine Intention to Interact in Vision-Based Interfaces. In Proceedings of the 32nd Annual SIGCHI Conference on Human Factors in Computing Systems (Toronto, Canada, April 26 – May 1, 2014). CHI ’14. ACM, New York, NY.

 paper  | video summary  | slides

Vision-based interfaces, such as those made popular by the
Microsoft Kinect, suffer from the Midas Touch problem:
every user motion can be interpreted as an interaction. In
response, we developed an algorithm that combines facial
features, body pose and motion to approximate a user’s
intention to interact with the system. We show how this can
be used to determine when to pay attention to a user’s actions and when to ignore them. To demonstrate the value of
our approach, we present results from a 30-person lab study
conducted to compare four engagement algorithms in single
and multi-user scenarios. We found that combining intention to interact with a “raise an open hand in front of you”
gesture yielded the best results. The latter approach offers a
12% improvement in accuracy and a 20% reduction in time
to engage over a baseline “wave to engage” gesture currently used on the Xbox 360

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