Markov models for ocular fixation locations in the presence and absence of colour

Kashlak, Adam ; Devane, E ; Dietert, H ; Jackson, H


In response to the 2015 Royal Statistical Society's statistical analytics challenge, we propose to model the fixation locations of the human eye when observing a still image by a Markov point process in R$_{2}$. Our approach is data driven using $\textit{k}$-means clustering of the fixation locations to identify distinct salient regions of the image, which in turn correspond to the states of our Markov chain. Bayes factors are computed as the model selection criterion to determine the number of clusters. Furthermore, we demonstrate that the behaviour of the human eye differs from this model when colour information is removed from the given image.