Watching you moving the mouse, i know who you are

Authors:
Chun Yu;Yue Shi;Xinliang Wang;Yuanchun Shi
Affiliations:
Tsinghua University, Beijing, China;Tsinghua University, Beijing, Beijing, China;Tsinghua University, Beijing, Beijing, China;Tsinghua University, Beijing, China
Venue:
CHI '12 Extended Abstracts on Human Factors in Computing Systems
Year:
2012

Citing 5
Cited 0

The influence of muscle groups on performance of multiple degree-of-freedom input

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Refining Fitts' law models for bivariate pointing

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Differences in pointing task performance between preschool children and adults using mice

ACM Transactions on Computer-Human Interaction (TOCHI)
A probabilistic approach to modeling two-dimensional pointing

ACM Transactions on Computer-Human Interaction (TOCHI)
Dynamic detection of novice vs. skilled use without a task model

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

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%.