This master thesis report describes the work of evaluating the approach of using an eye-tracker and machine learning to generate an interaction model for clicks. In the study, recordings were done from 10 participants using a quiz application, and machine learning was then applied. Models were created with varying quality from a machine learning view, although most models did not work well for interaction. One model was created that enable correct interaction 80\% of the time, although the specific circumstances for success were not identified. The conclusion of the thesis is that the approach works in some cases, but that more research needs to be done to evaluate general suitability, and approaches to make it work reliably.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-121834 |
| Date | January 2015 |
| Creators | Stenström, Albin |
| Publisher | Linköpings universitet, Interaktiva och kognitiva system |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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