Classifying Head Movements to Separate Head-Gaze and Head Gestures as Distinct Modes of Input

Hou, Baosheng James and Newn, Joshua and Sidenmark, Ludwig and Khan, Anam Ahmad and Bækgaard, Per and Gellersen, Hans (2023) Classifying Head Movements to Separate Head-Gaze and Head Gestures as Distinct Modes of Input. In: Proceedings of the 2023 CHI Conference on Human Factors in Computing :. ACM, New York, 253:1-253:14. ISBN 9781450394215

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Abstract

Head movement is widely used as a uniform type of input for human-computer interaction. However, there are fundamental differences between head movements coupled with gaze in support of our visual system, and head movements performed as gestural expression. Both Head-Gaze and Head Gestures are of utility for interaction but differ in their affordances. To facilitate the treatment of Head-Gaze and Head Gestures as separate types of input, we developed HeadBoost as a novel classifier, achieving high accuracy in classifying gaze-driven versus gestural head movement (F1-Score: 0.89). We demonstrate the utility of the classifier with three applications: gestural input while avoiding unintentional input by Head-Gaze; target selection with Head-Gaze while avoiding Midas Touch by head gestures; and switching of cursor control between Head-Gaze for fast positioning and Head Gesture for refinement. The classification of Head-Gaze and Head Gesture allows for seamless head-based interaction while avoiding false activation.

Item Type:
Contribution in Book/Report/Proceedings
Uncontrolled Keywords:
Research Output Funding/yes_externally_funded
Subjects:
?? yes - externally fundedno ??
ID Code:
189056
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Deposited On:
21 Mar 2023 11:35
Refereed?:
Yes
Published?:
Published
Last Modified:
09 Jul 2024 00:43