Depth perception and motion cue based 3D video quality assessment
Abstract: In this paper, we propose a depth perception and motion cue based three-dimensional (3D) video quality assessment (VQA). Depth perception provides the real 3D impression during viewing the 3D video (3DV), and motion cue is also important factor to simulate a Human Visual Systems (HVS) for 3DV. We combine the depth perception and motion cue, and generate a weighting map for 3D VQA. For adjusting contribution of every index in traditional VQA which are unsuitable for 3D VQA, we propose the weighting map based Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM) to evaluate the quality of 3DV. In experimental results section, the proposed 3D VQA have been validated using both our subjective test scores as well as traditional VQA. Our proposed method yields high correlation with measured Mean Opinion Score (MOS) and consistent performance in an asymmetric coding condition.
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