基于视觉显著性图的立体图像视疲劳评价

随着立体显示技术的飞速发展,立体图像带来的视疲劳问题引发了人们的广泛关注.视觉显著性区域决定着立体图像的性质,而双目视差和观看时间是影响立体图像视疲劳程度的两个重要因素.为了评价观看立体图像后产生的视疲劳,提出了立体图像视疲劳的评价模型.该模型基于视觉显著性图,根据视差和观看时间得到对立体图像视疲劳的评价.生理心理实验表明,该模型预测结果的可靠率到达了93％以上,依据该评价模型可由视差和观看时间快速、准确地评价立体图像视疲劳,为立体图像视疲劳的评价及立体图像的改进提供了依据.     

视差与空间频率对自由立体显示器观看舒适度的影响

观看舒适度是评价自由立体显示器性能的重要指标。立体图像的视差和空间频率影响人眼的感知深度,从而对观看舒适度有重要作用。本文采用3DS MAX三维建模软件和Photoshop图像处理软件得到不同视差和空间频率的立体图像,通过观看舒适度的客观度量结合主观评价确定视差及空间频率与观看舒适度的关系,得出观看舒适度较高时的视差范围和与之相对应的空间频率范围。实验表明,立体图像低空间频率所致的模糊可以增加观看舒适度。     

立体电视不同视差平面上的立体视锐度研究

通过生理感知试验,研究了双路立体电视不同视差平面上的立体视锐度.根据试验结果,人眼在0°视差平面上有最佳的立体视锐度,且随着画面中物体视差逐渐增大,人眼在观看该出/入屏物体时的立体视锐度将逐渐下降.此外,相比入屏物体而言,人眼在观看具有相同大小视差的出屏物体时具有更佳的立体视锐度.     

狭缝光栅自由立体显示器的立体图像串扰度

为了表征狭缝光栅自由立体显示器存在的左右眼视差图像的混叠程度,提出了立体图像串扰度C的概念。根据狭缝光栅自由立体显示器的结构和工作原理,应用几何光学知识,分析得出了立体图像串扰度C的计算公式,并给出了一个具体的狭缝光栅自由立体显示器的计算结果。通过观看实验,证明了所定义的立体图像串扰度C可以定量描述观看者在立体可视区域看到的立体图像的串扰程度。     

采用光栅的立体图像显示

近年来,有关动态立体图像显示系统的报道非常多.研究人员采用光栅(衍射光栅)阵列和液晶显示(LCD)相组合的简单结构,研制出无需眼镜可以多视差同时显示的动态立体图像显示系统(三维视频系统).该系统可以同时显示多方位全色视差图像,观看者无需选择视点位置,即可观看到全色立体图像.1 工作原理采用衍射光栅的三维视频系统的立体图像显示,在原理上实现了在各个不同的方向可以显示与各个方向相对应的视差图像.这种方法,通过增加视差图像的个数,一旦使视点移动,便可观察到转过来的图像,具有更自     

视差式立体信息采集、感知几何模型及舒适观看区研究综述

近年来,立体影视产业蓬勃发展,基于视差的立体成像技术成为市场主流.但是,基于视差的立体成像技术存在深度畸变、视觉不舒适等问题.针对这些问题,本文研究了立体视频系统几何模型与舒适观看区.首先,总结并比较了立体采集系统的各种配置模式;接着讨论了平移式立体系统中拍摄空间到感知空间的映射关系,即畸变模型,并用形状、深度畸变因子解释了木偶剧效应和纸板效应;然后分析了舒适观看区,对其三种定义做了比较,并基于国际上普遍采用的1°视差计算得出了舒适观看区域的几何范围;最后,本文将畸变模型和舒适观看区相关联,总结了立体图像拍摄应遵守的基本准则.     

一种基于视点分段式体像素的具有100°正面观看视角的桌面式光场显示系统

提出了一种基于视点分段式体像素的大视角全视差桌面式光场显示系统,采用了定向准直背光和反贴于分辨率为7680 pixel×4320 pixel的液晶显示屏上的柱镜阵列,实现了100°的水平观看视角,并利用光学偏折膜和全息功能屏,在适用于桌面显示的正面观看范围内实现了离散采样光场的体像素重建。设计了一种能够根据多位观看者的空间坐标划分独立视区的视点分段式体像素,并推导了其与液晶显示屏上子像素的函数映射关系,实现了对观看区域的分段式图像编码。提出了一种可为处在不同观看区域的多位观看者同时提供正确全视差光场显示的透视关系校正方法,填补了光学系统固有的垂直视差缺失,实现了桌面式光场显示中错误透视关系的自适应实时校正。     

立体图像视差自适应调整算法

针对不同尺寸立体显示器播放立体视频时立体视觉效果存在的差异,提出一种通过调节图像水平视差改善立体显示效果的方法。首先应用立体匹配算法得到立体图像初始视差,通过图像分割与连通性检测从中可靠地获取水平视差范围;为保证图像中全部景物在舒适立体融像区内成像,根据显示器尺寸与观看距离,调整左右眼图像在原立体视频中相对位置,形成合理的水平视差,从而在立体显示器上产生舒适的立体视觉效果。实验证明,本文提出的方法可自适应地调整立体图像的水平视差并较好地改善立体显示效果。     

立体图像对校正技术在三维显示中的应用

基于相机阵列的立体视差图像获取是3D立体显示技术的关键步骤之一,它为立体显示提供了丰富多彩的图像源;由于平行摆放的阵列相机拍摄得到的视差图像没有梯形失真和垂直视差,经3D显示设备后不会使观众产生视疲劳,因此,人们在视差图像获取时常采用时平行摆放的相机阵列.然而,在实际的操作中是很难达到这样理想的条件;本文针对常用的非平行摆放的双相机,经由图像校正的处理方法,来获得相同条件下平行式相机拍摄的效果;通过实验表明,该方案简单易行,效果良好,经3D自由立体显示后,观看的舒适度得到了提高.     

基于多种眼动行为的裸眼3D显示视觉疲劳评估方法

在裸眼3D立体视频观看中，由于存在辐辏调节的矛盾，观看者会产生诸如眩晕、呕吐等视疲劳症状，尤其在医疗、A/VR等场景下，3D视频观看通常为任务驱动，眼动行为由于受到主观控制，单一的眼动特征很难准确评估视觉疲劳，更无法得到视疲劳等级，导致视疲劳无法及时被发现，从而造成不可预估的损失。针对以上问题，本文提出了一种基于多种眼动行为的3D视疲劳等级评估模型，旨在观看3D内容时，通过对注视、扫视、眨眼等眼动行为进行建模分析，得到实时视疲劳等级。本文采用主客观相结合的方法进行实验：受试者观看3D内容，实验人员记录受试者主观打分并利用眼动仪提取受试者客观眼动行为；通过进行相关性分析，探究任务驱动下能够表征3D视疲劳的各种客观眼动行为；利用神经网络建立基于16种眼动行为的视疲劳四等级评估模型。模型对3D视疲劳等级的预测准确率达到82%，证明了模型的有效性。     

Repeated vergence adaptation causes the decline of visual functions in watching stereoscopic television

To evaluate visual fatigue when viewing stereoscopic TV, a technology expected to become the broadcasting display system of the future. Wide public acceptance of stereoscopic TV awaits resolution of many issues, including visual fatigue on viewing TV images. Visual fatigue was induced using a visual function simulator, consisting of prism and lens optical systems, while viewing stereoscopic TV. We assessed subject visual fatigue through subjective reports of symptoms and by the changes in visual functions. These functions included: viewer B [Js fusional break point, recovery point, accommodation step response, and visual evoked cortical potentials (VECP)]. Significant changes of some visual functions were found after watching simulated stereoscopic TV when the vergence load was heavy or when it changed over time; relative vergence limits decreased and the latency of VECP increased after watching, reflecting visual fatigue. After subjects rested, relative vergence limits recovered to pre-viewing levels. Our findings lead us to conclude that, aside from excessive horizontal binocular parallax, discontinuous changes in parallax is also a major factor that contributes to visual fatigue in the viewing of stereoscopic images. It also causes a decreased range of relative vergence, accommodation response, and a delay in the P100 latency of VECP.     

自由立体显示拍摄系统中摄像机空间自由度的确定

自由立体显示器的立体显示效果与视差图的视差大小及性质密切相关,而视差的大小是受获取视差图时相机的摆放方式影响的。文章提出利用双目相机标定技术求解左右摄像机中心的空间位置关系以及两个摄像机光轴的空间夹角,并通过标定结果不断调节摄像机的位置,从而使两个摄像机光轴达到近似平行,此时获取的视差图就可以保证更好的立体显示效果。通过实验研究得到了两个相机空间夹角允许的变化范围。该研究结果可用于指导自由立体显示器拍摄系统的调节。     

基于双目能量模型的立体图像质量客观评价方法

立体图像的深度感知取决于双目差距,基础视觉皮层的差距调谐细胞在感知立体深度的过程中起着关键作用.单只眼睛感知的图像信息被单目简单细胞接收之后传入双目简单细胞进行处理,继而被送入复杂细胞进行综合,得到基础视觉皮层对于一幅立体图像的能量响应.用数学模型来仿真简单的以及复杂的细胞对于双目差距的响应,并通过双目能量模型的计算达到评价彩色立体图像的目的.实验结果表明,双目能量模型的评价结果与立体图像的主观评价值具有较高的一致性.     

基于时空一致性的立体视频稳像改进方法

随着立体拍摄设备的普及,立体影视的后期稳像需求大大增加.直接观看带有抖动的立体视频,极易造成视觉疲劳.利用传统2D稳像方法分别稳像合成的立体视频很可能引入新的垂直视差,并且会导致水平视差的不稳定,大大影响视觉体验.因此,提出了一种改进的立体视频稳像方法,在3D运动模型进行单目稳像的基础上,增强两路视频的时空一致性约束,更好地稳定水平视差及消除垂直视差.最后对稳定后的序列进行合理的裁切放大.对几组不同的立体抖动视频进行了试验,测试结果表明所提出的方法是有效的.     

Three-dimensional imaging methods based on multiview images

Three-dimensional imaging methods, based on parallaxes as their depth cues, can be classified into the stereoscopic providing binocular parallax only, and multiview providing both binocular and motion parallaxes. In these methods, the parallaxes are provided by creating a viewing zone with use of either a special optical eyeglasses or a special optical plate as their viewing zone-forming optics. For the stereoscopic image generations, either the eyeglasses or the optical plate can be employed, but for the multiview the optical plate or the eyeglasses with a tracking device. The stereoscopic image pair and the multiview images are presented either simultaneously or as a time sequence with use of projectors or display panels. For the case of multiview images, they can also be presented as two images at a time according to the viewer's movements. The presence of the viewing zone-forming optics often causes undesirable problems, such as appearance of moire/spl acute/ fringes, image quality deterioration, depth reversion, limiting viewing regions, low image brightness, image blurring, and inconveniences of wearing.     

平行式双目立体系统基线长度的选取

如何获取人眼立体融合范围内的视差图像是立体影像获取的前提,而视差的大小与双目立体相机间的基线长度存在一定关系.通过分析平行式双目立体系统产生视差的原理,并结合人眼Panum融合区对立体拍摄过程中基线长度的取值进行限定.最后通过实验对推导结果进行验证.该研究可对实际立体影像拍摄过程中相机间隔的选取提供参考.     

Two-stream interactive network based on local and global information for No-Reference Stereoscopic Image Quality Assessment

Nowadays, stereoscopic image quality assessment (SIQA) based on convolutional neural network (CNN) has become the mainstream model of image quality assessment (IQA). Compared with the two-dimensional quality evaluation model, stereoscopic image quality evaluation is more challenging due to the effects of depth and parallax information. In this paper, we propose a two-stream interactive network model to perform quality evaluation, which can well simulate the process of human stereo visual perception. Meanwhile, we enhance the extraction of local and global features of images by asymmetric convolution kernel and interactive sub-networks of inter-layers, respectively, which can further optimize our network model. Our proposed algorithm was evaluated on four public databases. The final experimental results show that our proposed algorithm exhibits good performance not only on the whole database but also on each single distortion type.     

No-reference Stereoscopic Image Quality Assessment Using Binocular Self-similarity and Deep Neural Network

Quality assessment of three-dimensional (3D) images is more challenging than that of 2D images. The quality of 3D visual experience is one of the most challenging areas of human binocular perception and is affected by multiple factors such as asymmetric stereo image/video compression, depth perception, visual discomfort, and single view quality. In this paper, we propose a new no-reference quality assessment method for stereoscopic images based on Binocular Self-similarity (BS) and Deep Neural Networks (DNN). To be more specific, a BS index is defined and computed according to binocular rivalry and suppression based on the depth image-based rendering technique. Then, a DNN is trained in an opinion unaware way to predict local quality. Binocular integration (BI) index is calculated by using the trained DNN, accounting for binocular integration behaviors. Finally, the final quality score of stereoscopic image is obtained by combining the BS and BI indexes together. Experimental results on four public 3D image quality assessment databases demonstrate that compared with existing methods, the proposed method can achieve high consistency with subjective perception on stereoscopic images with both symmetric and asymmetric distortions.