Elicitation study for a Smart Weather Station

Details

Supervisors

Vanderdonckt, Jean

Faculty

Louvain School of Management

Degree label

Master [60] en sciences de gestion

Abstract

More and more devices are being developed that allow applications to be controlled using gestures, as this has a number of advantages. However, defining the exact gestures for each command and application is not an easy task. In fact, the 3D dimension of gestures and their great diversity open up a wide range of possibilities and make them more difficult for people to learn. This thesis analyses which gestures would be the most intuitive for users, in order to have gestures that are as user-friendly as possible. The application chosen is that of a smart weather station, with fifteen associated instructions. These commands will mainly control functions that are specific to this application. The analysis will be carried out in relation to a possible real-life application using the Leap Motion Controller, an infrared camera capable of detecting hand gestures. In order to obtain the most intuitive gestures, an elicitation study is carried out as follows. In a preparatory phase, the fifteen instructions are identified and linked to referents (descriptions of the action and its result). Twenty-five participants are asked to perform a gesture for each instruction, which is recorded by the Leap Motion Controller. Each participant also gives a score out of seven to rate how well their gesture matches the referent. These gestures are then classified into forty categories, allowing general trends to be identified. For each instruction, the most frequent or two most frequent gestures are also identified.