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Visual Comfort Enhancement for Stereoscopic Video Based on Binocular Fusion Characteristics

机译:基于双目融合特性的立体视频视觉舒适度提升

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摘要

A well-known problem in stereoscopic videos is visual fatigue. However, conventional depth adjustment methods provide little guidance in deciding the amount of depth control or determining the condition for depth control. We propose a depth adjustment method based on binocular fusion characteristics, where the fusion time is used as the parameter for adjustment. Visual comfort enhancement is implemented with the horizontal image shift approach for depth adjustment. The speeded-up robust feature is used to estimate maximum disparity and disparity distribution, while a face detection algorithm is used to estimate the viewing distance with a single web camera. Binocular fusion characteristics are acquired in advance by measuring the time required for fusion under various conditions, including foreground disparity, background disparity, and focal distance for random-dot stereograms. Finally, a subjective evaluation is conducted in fixed and free-to-move viewing conditions, and the results show that comfortable videos were generated based on the proposed depth adjustment method.
机译:立体视频中的一个众所周知的问题是视觉疲劳。但是,传统的深度调节方法在确定深度控制量或确定深度控制条件方面几乎没有指导。我们提出了一种基于双目融合特性的深度调整方法,其中融合时间用作调整参数。视觉舒适度增强是通过用于深度调整的水平图像移位方法实现的。加速的鲁棒功能用于估计最大视差和视差分布,而人脸检测算法用于估计单个网络摄像机的观看距离。通过在各种条件下测量融合所需的时间来预先获得双眼融合特性,包括前景视差,背景视差和随机点立体图的焦距。最后,在固定和自由移动的观看条件下进行了主观评估,结果表明,基于提出的深度调整方法可以生成舒适的视频。

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