| Full text | |
| Author(s): |
Velloso, Eduardo
;
Morimoto, Carlos Hitoshi
;
ASSOC COMP MACHINERY
Total Authors: 3
|
| Document type: | Journal article |
| Source: | CHI '21: PROCEEDINGS OF THE 2021 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS; v. N/A, p. 13-pg., 2021-01-01. |
| Abstract | |
Motion correlation interfaces are those that present targets moving in different 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 and suggest guidelines for future work. (AU) | |
| FAPESP's process: | 17/50121-0 - AREThA: gaze interaction for the internet of things through augmented reality |
| Grantee: | Carlos Hitoshi Morimoto |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 16/10148-3 - Gaze-Based Interaction in Wearable Computing: an interface for the Internet of Things |
| Grantee: | Carlos Hitoshi Morimoto |
| Support Opportunities: | Regular Research Grants |