A gaze-based study for investigating the perception of visual realism in simulated scenes

Abstract

Visual realism has been a major objective of computer graphics since the inception of the field. However, the perception of visual realism is not a well-understood process and is usually attributed to a combination of visual cues and image features that are difficult to define or measure. For highly complex images, the problem is even more involved. The purpose of this paper is to present a study based on eye tracking for investigating the perception of visual realism of static images with different visual qualities. The eye-fixation clusters helped to define salient image features corresponding to 3D surface details and light transfer properties that attract observers' attention. This enabled the definition and categorization of image attributes affecting the perception of photorealism. The dynamics of the visual behavior of different observer groups were examined by analyzing saccadic eye movements. We also demonstrated how the different image categories used in the experiments were perceived with varying degrees of visual realism. The results presented can be used as a basis for investigating the impact of individual image features on the perception of visual realism. This study suggests that post-recall or simple abstraction of visual experience is not accurate and the use of eye tracking provides an effective way of determining relevant features that affect visual realism, thus allowing for improved rendering techniques that target these features.