Abstract
Visual comfort assessment for stereoscopic 3D video is of great importance for stereoscopic safety and health issue. In order to investigate visual discomfort induced by motion features in salient motion regions, we propose a visual comfort assessment metric that focuses on pixel-level motion features in salient motion regions. In our framework, we propose the pixel-level motion features extraction method based on point detector, Kanade-Lucas-Tomasi(KLT) feature tracker, and Salient Motion Depth Extraction (SMDE) approach. The motion features are spatially pooled and temporally pooled to predict visual comfort score. Subjective assessments have been conducted to evaluate our proposed visual comfort metric using natural stereoscopic videos. The experiment results have been demonstrated that our proposed visual comfort metric improves the correlation with subjective assessments.
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