Visual comfort assessment for stereoscopic 3D images based on salient discomfort regions

We propose visual comfort assessment for stereoscopic 3D (S3D) images based on salient discomfort regions. Color-based saliency successfully represents visual attention because that the human visual system (HVS) focuses on the most salient region in an image. Disparity-based saliency effectively expresses visual comfort in S3D images. Based on two saliencies, we extract salient discomfort regions which mostly determine the overall visual comfort degree in S3D images. Then, we predict the visual comfort score from salient discomfort regions by a disparity feature vector which combines saliency-weighted disparity and maximum disparity. Finally, we provide visual comfort index maps of S3D images based on visual comfort scores, thus showing perceptually salient discomfort regions and their degrees. Experimental results demonstrate that the proposed method achieves significantly high accuracy in visual comfort assessment as compared to existing methods.