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Adaptive Saliency-Weighted 2D-to-3D Video Conversion

机译:自适应显着加权2D-3D视频转换

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Creating 3D video content from existing 2D video has been stimulated by recent growth in 3DTV technologies. Depth cues from motion, focus, gradient, or texture shading are typically computed to create 3D world perception. More selective attention might be introduced using manual or automated methods for entertainment or educational purposes. In this paper, we propose an adaptive conversion framework that combines depth and visual saliency cues. A user study was designed and subjective quality scores on test videos were obtained using a tailored single stimulus continuous quality scale (SSCQS) method. The resulting mean opinion scores show that our method is favored by human observers in comparison to other state-of-the-art conversion methods.
机译:从现有的2D视频创建3D视频内容已被3DTV技术的增长刺激。通常计算来自运动,焦点,梯度或纹理着色或纹理着色的深度线索以创建3D世界感知。可以使用手动或自动化方法来推出更具选择性的娱乐或教育目的。在本文中,我们提出了一种适应性转换框架,它结合了深度和视觉显着性提示。使用量身定制的单刺激连续质量尺度(SSCQS)方法,设计了用户学习,并获得了测试视频的主观质量评分。由此产生的平均意见分数表明,与其他最先进的转换方法相比,我们的方法受人类观察者的青睐。

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