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

机译:基于显着不适区域的立体3D图像的视觉舒适性评估

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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.
机译:我们提出基于显着不适区域的立体3D(S3D)图像的视觉舒适性评估。基于颜色的显着性成功代表了视觉注意力,因为人类视觉系统(HVS)专注于图像中最显着的区域。基于差异的显着性有效地表达了S3D图像中的视觉舒适度。基于两个显着性,我们提取了显着的不适区域,这些区域主要决定了S3D图像的总体视觉舒适度。然后,我们通过结合显着性加权视差和最大视差的视差特征向量,预测来自显着不适区域的视觉舒适度评分。最后,我们根据视觉舒适度评分提供了S3D图像的视觉舒适度指数图,从而显示了感知上的显着不适区域及其程度。实验结果表明,与现有方法相比,该方法在视觉舒适性评估中具有很高的准确性。

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