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Eye movements and visual discomfort when viewing stereoscopic 3D content

机译:观察立体3D内容时的眼睛运动和视觉不适

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The visual brain fuses the left and right images projected onto the two eyes from a stereoscopic 3D (S3D) display, perceives parallax, and rebuilds a sense of depth. In this process, the eyes adjust vergence and accommodation to adapt to the depths and parallax of the points they gazed at. Conflicts between accommodation and vergence when viewing S3D content potentially lead to visual discomfort. A variety of approaches have been taken towards understanding the perceptual bases of discomfort felt when viewing S3D, including extreme disparities or disparity gradients, negative disparities, dichoptic presentations, and so on. However less effort has been applied towards understanding the role of eye movements as they relate to visual discomfort when viewing S3D. To study eye movements in the context of S3D viewing discomfort, a Shifted-S3D-Image-Database (SSID) is constructed using 11 original nature scene S3D images and their 6 shifted versions. We conducted eye-tracking experiments on humans viewing S3D images in SSID while simultaneously collecting their judgments of experienced visual discomfort. From the collected eye-tracking data, regions of interest (ROIs) were extracted by kernel density estimation using the fixation data, and an empirical formula fitted between the disparities of salient objects marked by the ROls and the mean opinion scores (MOS). Finally, eye-tracking data was used to analyze the eye movement characteristics related to S3D image quality. Fifteen eye movement features were extracted, and a visual discomfort predication model learned using a support vector regressor (SVR). By analyzing the correlations between features and MOS, we conclude that angular disparity features have a strong correlation with human judgments of discomfort. (C) 2018 Elsevier Inc. All rights reserved.
机译:视觉脑熔断到从立体3D(S3D)显示,从立体3D投射到两只眼睛上的左右图像,感知视差,并重建深度感。在这个过程中,眼睛调整血肿和住宿,以适应他们凝视的点的深度和视差。在查看S3D内容时,住宿与痛苦之间的冲突可能导致视觉不适。在查看S3D时,已经了解各种方法,以了解感知的不适的感知基础,包括极端差异或差异梯度,负差异,专题演示等。然而,在观看S3D时,较低的努力旨在了解眼球运动的作用,因为它们与视觉不适相关。为了在S3D观看不适的上下文中学习眼球运动,使用11个原始的自然场景S3D图像和6个移位版本构建Shifted-S3D-Image-Database(SSID)。我们对SSID中的S3D图像进行了关注的实验,同时收集他们经历的经验丰富的视觉不适的判断。根据收集的眼跟踪数据,利用固定数据通过内核密度估计提取感兴趣的区域(ROI),并且拟合由ROL标记的突出物体的差异和平均意见分数(MOS)之间的经验公式。最后,使用眼跟踪数据来分析与S3D图像质量相关的眼球运动特性。提取十五个眼睛运动特征,并使用支持向量回归(SVR)学习视觉不适预测模型。通过分析特征与MOS之间的相关性,得出结论,角度差距特征与人类判断的不适具有强烈相关性。 (c)2018年Elsevier Inc.保留所有权利。

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