An Objective Stereoscopic Image Visual Comfort Assessment Metric Based on Visual Important Regions

Stereo video technology provides depth perception and immersion visual experience, but it also makes people feel visual fatigue and causes the decrease of the experience quality. Therefore, how to evaluate the visual comfort of stereoscopic image/video effectively is still a research focus. In this paper, an objective visual comfort assessment metric based on visual important regions is proposed. First, the Visual Important Regions (VIR) are obtained from image saliency and disparity map information. Then, disparity amplitude, disparity gradient, and spatial frequency features are extracted and fused into a feature vector. Finally, the values of objective assessment are predicted by Support Vector Regression (SVR). Experimental results show that compared with existing methods, the proposed metric achieves higher consistency with subjective visual comfort assessment of stereoscopic images.