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An Information Theoretic Mouse Trajectory Measure

  • Samuel Epstein
  • Eric S. Missimer
  • Margrit Betke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6766)

Abstract

In this paper, we propose the Relative Trajectory Information (RTI) measure, an information theoretic measure to evaluate mouse pointer trajectories. The measure is used to score the level of smoothness of mouse pointer trajectories. We show that, by leveraging Gaussian processes and information theory, RTI accounts for relative differences in timestamps of the mouse pointer trajectories. RTI also does not require explicit descriptions of targets, in either their location or size. Our experimental analysis shows how RTI can capture the motion signature of a user with severe motion disabilities and distinguish it from the motion signature of smooth trajectories obtained in a control experiment.

Keywords

Gaussian Process Multivariate Gaussian Distribution Differential Entropy Mouse Pointer Information Theoretic Measure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Samuel Epstein
    • 1
  • Eric S. Missimer
    • 1
  • Margrit Betke
    • 1
  1. 1.Image and Video Computing Group, Computer Science DepartmentBoston UniversityBostonUSA

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