@conference {6137, title = {Tracking Visitor\&$\#$39;s Fields of Interest in Large Scale Art Installations}, booktitle = {IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC)}, year = {2013}, pages = {852-857}, abstract = {

Aurora is a large-scale kinetic art installation that reacts to human presence directly, with sensors triggering outputs, and indirectly, by modifying output behaviour rules. This paper describes a novel method for estimating visitors{\textquoteright} fields of interest, their attention to specific parts of the installation, with a future goal of using this measure as a fitness function for output behaviour modification based on genetic algorithms. Due to constraints in Aurora, distributed overhead distance sensors were used as the sensory inputs. A low resolution height graph of the space below the installation is created, and the active sensors are clustered into groups. The height graph and sensor groups are used to produce a probability map of possible visitor locations. Based on these, particle filters are created to estimate the visitors{\textquoteright} state, and by extension their fields of interest. Using this overall strategy for tracking and interest prediction, an average prediction accuracy of 92\% is found when compared to a set of simulated people moving within a simulated space.

}, url = {https://doi.org/10.1109/SMC.2013.150}, author = {Brandon J DeHart and Rob Gorbet} }