A Bayesian Network Model of a Collaborative Interactive Tabletop Display

In this paper, I explore the use of Bayesian Networks to model the use of an interactive tabletop display in a collaborative environment. Specifically, this model is intended to extract user-profile information for each user including their location at the table as well as their handedness. The network uses input from a six-degrees-of-freedom stylus device as its source of observable information. This paper introduces a first attempt at a model to support these requirements as well as a preliminary evaluation of the model. Results show that the model is sufficiently accurate to obtain a user profile in real time in a Tabletop Display environment.