Visual perception and sequences of eye movement fixations: a stochastic modeling approach

Sequences of visual fixations, while looking at an object, are modeled as Markov processes, and statistical properties of such processes are derived by means of simulations. The sequences are also abstracted as character strings, and a quantitative method of measuring their similarity, based on minimum string editing cost (actually dissimilarity distance), is introduced. Interrelationships between the structure and size of the generating Markov matrices and the string editing distance shed light on the relative roles of deterministic and probabilistic processes in producing human visual scanpaths.< >