Visualizing the Perceived Discomfort of Stereoscopic Video

Abstract

Visual discomfort prediction is of importance for image safety issue in stereoscopic displays. This paper proposes automatic visualization of the perceived discomfort for stereoscopic video contents. The proposed method makes effective use of saliency-based measures for visual importance analysis in video scenes. Based on the analysis of visual importance, we quantify and visualize the visual discomfort induced by disparity and motion characteristics of stereoscopic video contents. The proposed method outputs visual importance-based comfort maps that allow users to monitor which regions in each video frame are perceptually significant and problematic with respect to visual discomfort. Experimental results have demonstrated the effectiveness of the proposed method by subjective assessments using various types of stereoscopic videos with diverse disparity and motion characteristics.