Conference Proceedings

A probabilistic interpretation of motion correlation selection techniques

E Velloso, CH Morimoto

Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems | Published : 2021


Motion correlation interfaces are those that present targets moving in diferent patterns, which the user can select by matching their motion. In this paper, we re-formulate the task of target selection as a probabilistic inference problem. We demonstrate that previous interaction techniques can be modelled using a Bayesian approach and that how modelling the selection task as transmission of information can help us make explicit the assumptions behind similarity measures. We propose ways of incorporating uncertainty into the decision-making process and demonstrate how the concept of entropy can illuminate the measurement of the quality of a design. We apply these techniques in a case study a..

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