Previous research on modeling human's pointing behavior focuses on user-independent variables such as target width and distance. In this work-in-progress, we investigate a set of user-dependent variables, which are drawn from cursor trajectory data and may represent an individual user's unique pattern when controlling mouse movement. Using these features, the 8 users in our experiment can be recognized at a promising accuracy as high as 87.5%.
展开▼
