and Bart de Boer

Humans are very sensitive to symmetry in visual patterns. Symmetry is detected and recognized very rapidly. While viewing symmetrical patterns, eye fixations are concentrated along the axis of symmetry or the symmetrical center of the patterns. This suggests that symmetry is a highly salient feature. Existing computational models of saliency, however, have mainly focused on contrast as a measure of saliency. These models do not take symmetry into account. In this paper, we discuss local symmetry as a measure of saliency. We developed a number of symmetry models and performed an eye tracking study with human participants viewing photographic images to test the models. The performance of our symmetry models is compared with the contrast saliency model of Itti et al. [1]. The results show that the symmetry models better match the human data than the contrast model. This indicates that symmetry is a salient structural feature for humans, a finding which can be exploited in computer vision.