Gaze quality assisted automatic recognition of social contexts in collaborative Tetris

Authors:
Weifeng Li;Marc-Antoine Nüssli;Patrick Jermann
Affiliations:
CRAFT, Swiss Federal Institute of Technology, Lausanne (EPFL), Switzerland;CRAFT, Swiss Federal Institute of Technology, Lausanne (EPFL), Switzerland;CRAFT, Swiss Federal Institute of Technology, Lausanne (EPFL), Switzerland
Venue:
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
Year:
2010

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Abstract

The use of dual eye-tracking is investigated in a collaborative game setting. Social context influences individual gaze and action during a collaborative Tetris game: results show that experts as well as novices adapt their playing style when interacting in mixed ability pairs. The long term goal of our work is to design adaptive gaze awareness tools that take the pair composition into account. We therefore investigate the automatic detection (or recognition) of pair composition using dual gaze-based as well as action-based multimodal features. We describe several methods for the improvement of detection (or recognition) and experimentally demonstrate their effectiveness, especially in the situations when the collected gaze data are noisy.