Markov Models for Ocular Fixation Locations in the Presence and Absence of Colour
针对2015年皇家统计学会挑战，用马尔可夫点过程建模人眼注视静止图像的位置，通过k均值聚类识别显著区域作为马尔可夫链状态，并用贝叶斯因子选择聚类数，发现去除颜色后眼动行为偏离模型。
Summary 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 R2. Our approach is data driven using 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.