Eigenplaces for Segmenting Exhibition Space
Kingkarn Sookhanaphibarn, Ruck Thawonmas, Frank Rinaldo · 2012
In this paper, we aim at segmenting exhibition space inherent in circulation behavior of visitors in a museumlike environment such as a virtual gallery in Second Life or even a real museum at MIT. The segmentation of exhibition space can be achieved with eigenplaces, which is the eigendecomposition of the covariance matrix of the characteristic vectors obtained from visitor dwell time for each time slot. Eigenplaces take advantage of the capability of showing the (first, second, third, and forth) most important circulation behavior of visitors as well as examining the degree of dominance of their corresponding. We, then, adopted the theory of graph spectra for partitioning the exhibit spaces. In experiments, we applied the segmentation approach to the data set obtained from the virtual and real museums: 36 avatars at the Ritsumeikan gallery in Second Life and 45 real visitors at the MIT museum in order to discovering groups of strongly coherent exhibits.