An application of support vector machines and symmetry to computational modeling of perception through visual attention

摘要

Eye movement is connected with attention and visual perception. Our previous research provided a computational model for detection of symmetry, and a case was made for a dynamic model of symmetry detection based on adaptive saccades and visual attention. Here, we present computational model of saccade target selection and simulate its action in the context of perception of global periodic symmetry of surfaces using local (foveal) symmetry approma- tions to direct saccadic eye movements. Target selection is modeled via support vector machine regression. The motivation for support vector model finds its justification in the properties of the superior colliculus.