三维显示信息重建及评价方法研究
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摘要
我们所处的世界是个真实的、立体的、三维的世界。从古时人们用绘画记录身边或头脑中的影像，到照相机的诞生，再到摄像机的诞生，人们对于记录的追求从未停止。当平面记录影像的壁垒被阿凡达给人们带来的震撼彻底撼动后，三维显示真正变得家喻户晓，成为显示领域新的大众化追求。
三维显示技术的基本原理是利用人的双眼视差所观察到的左右眼不同的图像在大脑中形成立体视觉。因此，三维显示的核心技术其实就是如何产生左右眼图像与如何让观看者的左右眼只看到各自的图像。当左右眼同时观看物体时，因为左右眼双目视差（binocular parallax）的存在使得左右眼接收不同角度的图像，再经过大脑合成后使人们产生物体立体感。
三维显示在21世纪伊始带给人们视觉震撼享受之后，人们迫切渴望能够更多的享受到三维显示带给他们的快乐。但是，大规模应用对于现阶段三维显示技术还不能实现，最大的原因即是三维显示片源严重不足。高精密度的三维摄像机虽然可以拍摄任何想要获取的三维场景，可用于电影电视制作，但是使用这种方法获取三维视频却有成本高，制作周期难的困扰，难以普及。同时，面对丰富并且制作简单的传统二维图像及视频，人们也希望能够重温同样内容下的三维震撼效果。三维显示信息重建的想法自此萌生。
三维显示信息重建，即二维转三维，是通过软件算法的方式将二维的图像或视频转换成人们可以接受的具备三维显示效果的图像及视频。在转换的过程中，要使用到深度图像序列（简称深度图）信息。深度图是三维显示区别于二维显示的差异信息，幅二维图像如果有了深度信息的配合就可以通过基于深度图像绘制技术（depth image basedrendering-DIBR），将幅二维图像转换为三维图像。这种方法的出现在理论上提出了切实可行的突破目前制约三维显示产业发展瓶颈的方法。
研究者们自21世纪起便开始了这方面的研究，也取得了些喜人的进展。本文在前人研究基础上，首先概要的回顾了三维显示的发展史。接下来介绍了本文研究所需要的背景知识：包括人眼立体视觉基本机理，三维显示技术原理和分类。在人眼立体视觉基本机理中分单目感知深度和双目视差感知深度两类介绍。在三维显示技术原理和分类中按照眼镜式三维显示技术、裸眼三维显示技术、广义三维显示技术的顺序详细总结了领域内现行有效的三维显示技术原理及分类。
其次，全面的研究总结了现阶段产业领域内三维显示信息重建技术研究现状和所面临的问题。指出了三维显示信息重建技术的现实意义。基于对比分类的方法明确提出了三维显示信息重建（二维转三维）技术在全部的三维显示视频获取方法中的地位及意义。介绍了深度图的概念，详细描述了基于深度图的三维图像渲染技术（DIBR）。并站在二维转三维技术实际需要的角度，分析了二维转三维所需要的视频处理工具及研究现状。其中包括图像边缘检测算法、图像分割算法、模式识别、视频跟踪等。
遵循基于深度图渲染三维图像的逻辑，本文第三部分展开了探索工作，提出了套二维图像转换三维图像的视频处理系统。首先对图像进行预处理，包括二维图像获取、双边滤波。实验证明，本文应用双边滤波的方法对二维图像进行预处理有效的降低了二维转三维步骤的错误率。接下来，我们使用K-means聚类算法对预处理过后的图像进行分类，从而得到前景背景分离的等待赋予深度的图像。为了更准确的对经过聚类算法处理后的图像像素赋予深度，我们提出了基于经验性的图像布局模型，用于对图像中各目标区别性的做出深度赋值。实验证明，所提方式探索了种图像二维转三维的可行性方法，并为之后的研究奠定了定的理论基础。
我们还提出了种具有良好交互操作性的、半自动的基于二维视频获取三维视频关键信息的系统，在系统中，提出了基于目标跟踪算法完成非关键帧的深度图自动生成算法。系统可用于生成三维视频所需的深度信息。首先将视频提取关键帧，对关键帧进行基于懒惰抠图(lazy snapping)算法的图像分割。之后交互的将关键帧的主要目标进行标记，标记目标的深度信息随之赋值。对于非关键帧，根据关键帧的深度图，使用我们所提出的基于目标跟踪的非关键帧图像深度自动生成算法自动化的生成。最后，二维视频序列所对应的深度图像序列全部生成。我们在章节末尾提出了种二维转三维的系统框架。实验表明，我们提出的基于目标跟踪的非关键帧图像深度自动生成算法处理结果正确，能够生成较好的二维图像对应的深度图。
我们在研究二维转三维算法及系统的同时，考虑到目前三维显示产业尚属推广阶段，研究并提出了全面的立体电视图像质量测试方法。鉴于目前产业发展阶段实际需要，主要针对眼镜式三维显示提出平板立体电视机及平板立体显示器的立体图像质量的测量条件和测量方法。我们从工作条件、结果的表示、环境条件、电源、稳定时间、测试场地、测量位置、信号格式、测试信号、测量点和测量项目、测试仪器、标准测试状态等方面对立体电视图像质量的测试要求做出了全面的研究与规定。并提出了标准的测量方法用于参考。研究成果已经形成行业标准文本。
此外，我们基于测量不确定度的概念，对该领域内公认的能够产生接近标准的视频信号的广播电视测试信号发生器（SFU）进行了关于机顶盒电平指标测试的测量不确定度研究。提出了广播电视测试信号发生器的A类、B类测量不确定度评定方法。所提出的评价方法及实验所得结果可作为立体电视图像质量评价的测量不确定度评估依据。
最后结合产业应用实际，为了适应产业发展需求，提出了家庭网络系统体系结构和参考模型。适用于有三维显示及高清互动诉求的家庭或类似的室内场所的网络构建。并提出了种基于家庭内部电力线载波的网络融合解决方案。相关成果已形成国家标准报批。
The world we live in is a real, three-dimensional (3D) space. From ancientpainting recording image around or in mind, to the birth of a camera and videotape recorder, people never stopped pursuing more vivid and lively record ofthe world. When "Avatar" shock up the notion of traditional2-D images,3-Ddisplay became a household name and a new popular pursuit in the displayarea.
After enjoying the stunning visual shock of3-D images at the beginningof the21st century, people are eager to get more. However, large scale use of3-D display is still a challenge by now. Scarcity of3-D film sources is the mostimportant reason. The high-precision3-D camera can shoot any scene and usedfor3-D film and television production, but it is hard to widely spread due tohigh cost and long production cycle. At the same time, facing abundant andeasy making2-D images and videos, people also want to relive the samecontent under the3D shock effect. Therefore, the technology of3-Dinformation reconstruction came out.
The3-D display information reconstruction technology, i.e.2D-3Dconversion, is to convert2-D images or videos to acceptable3-D display ofimages and video through software algorithm. In the conversion process, thedepth of the image sequence (i.e."depth map") will be used. Depth map isinformation gap between2-D display and3-D display. When adding depth map,a2-D image will be able to convert to3-D image by using renderingtechnology based on depth (DIBR-depth image based rendering).Theoretically,this is a practical approach to breakthrough the bottleneck of3D industrydevelopment–lack of sources.
Related research started since the very beginning of21th century. Thereare also many encouraging research progress in this field. This paper, inChapter1, reviews the previous research of3-D technology, then introducesbackground knowledge of the research methods in our work, included basicprinciple of human eyes vision, principle and classification of3D displaytechnology. There are single eye depth perception and binocular parallax depth perception. We make a detailed analysis from three aspects, glassed typed3-Ddisplay, naked eyes typed3-D display and generalized3-D display；
In Chapter2, this paper summarizes current research status of3-D displayinformation reconstruction and industry problems at this stage；meanwhile,points out the important status and realistic significance of3-D displayinformation reconstruction techniques in whole3-D video capture process.This chapter introduces concept of depth map, describes3-D image renderingtechniques based on depth map (DI BR) in detail, and analyzes current videoprocessing tools and research status in2D-3D conversion, including imageedge detection algorithm, image segmentation algorithms, pattern recognitionand video tracking.
Following the logic of depth map based3-D rendering, Chapter3describeour exploration of a new2D-3D conversion system. The first step ispre-processing, including2-D image acquisition and bilateral filtering.Experiments show that bilateral filtering method we use in this paper for2-Dpreprocessing effectively lowered the error rate in2D-3D conversion. Afterthat, we classify objects in the image which has been pro-processed usingk-means clustering algorithm, and then image which foreground andbackground is divided and waiting for assigning depth value would be gotten.In order to assign depth value to the image more accurately, we propose layoutmodel of image which has been processed using k-means clustering algorithm.Experiment results shows that the method we proposed has explored anavailable2D to3D method, and laid the groundwork for future research.
We also propose a semiautomatic, interoperability system through whichkey information of3D video from2D video can be captured. In the system,automatic generation method of non-key frames depth map base on objecttracking algorithm has been proposed. The system can be used to generatedepth information which generation of3D video required. First, get key framefrom video, do image segmentation based lazy snapping algorithm on keyframe, then label main object in key frame interactively, depth value will begiven after that. For non-key frames, according to depth map of key frames, weuse generation method of non-key frames depth map base on object trackingalgorithm which we proposed to generate depth map of non-key frame automatically. Finally, depth image sequence which corresponds to2D videosequence has been generated. We propose2D to3D system framework at theend of this chapter. The experimental results show that the generation methodof non-key frames depth map base on object tracking algorithm which wepropose can get correct result, depth map generation using this algorithm hasgood performance.
While making deep research of2D to3D algorithms and system,considering3D display industry is still at the stage of promotion, we proposecomprehensive method of measurement for the image quality of3DTV. In viewof actual needs of this industrial development stage, we propose measurementconditions and measurement method for quality of flat panel stereo TV and flatpanel stereo terminal in the type of glassed3D display. We makecomprehensive research and rule on image quality of3DTV measurementrequirement. Include following aspects, working conditions, environmentalpresentation, power, stable duration, measurement site, measurement position,format of test signal, measurement points and measurement points,measurement instruments, standard test status. And we raise reference standardmeasurement methods. Research results have formed the industry standardtext.
In addition, based on the concept of measurement uncertainty, this paperstudies the measurement uncertainty of set-top box’s electrical level test byusing SFU (Single Family Unit)-one kind of broadcast test system instrumentwhich is widely considered can generate more-or-less standard video signals.We propose evaluation methods aim at A-class and B-class measurementuncertainty respective. The evaluation methods and the experimental result canbe applied to evaluate image quality of3-D television.
At last, we combined with the actual industry application experience,designs a family network system architecture and reference model which ismore adaptable in real family network construction scenarios in demanding of3-D display and high definition interactions. We also proposed a networkconvergence solution based on indoor Power-Line Carrier (PLC) network,which is already in approval process for national standards.
三维显示技术的基本原理是利用人的双眼视差所观察到的左右眼不同的图像在大脑中形成立体视觉。因此，三维显示的核心技术其实就是如何产生左右眼图像与如何让观看者的左右眼只看到各自的图像。当左右眼同时观看物体时，因为左右眼双目视差（binocular parallax）的存在使得左右眼接收不同角度的图像，再经过大脑合成后使人们产生物体立体感。
三维显示在21世纪伊始带给人们视觉震撼享受之后，人们迫切渴望能够更多的享受到三维显示带给他们的快乐。但是，大规模应用对于现阶段三维显示技术还不能实现，最大的原因即是三维显示片源严重不足。高精密度的三维摄像机虽然可以拍摄任何想要获取的三维场景，可用于电影电视制作，但是使用这种方法获取三维视频却有成本高，制作周期难的困扰，难以普及。同时，面对丰富并且制作简单的传统二维图像及视频，人们也希望能够重温同样内容下的三维震撼效果。三维显示信息重建的想法自此萌生。
三维显示信息重建，即二维转三维，是通过软件算法的方式将二维的图像或视频转换成人们可以接受的具备三维显示效果的图像及视频。在转换的过程中，要使用到深度图像序列（简称深度图）信息。深度图是三维显示区别于二维显示的差异信息，幅二维图像如果有了深度信息的配合就可以通过基于深度图像绘制技术（depth image basedrendering-DIBR），将幅二维图像转换为三维图像。这种方法的出现在理论上提出了切实可行的突破目前制约三维显示产业发展瓶颈的方法。
研究者们自21世纪起便开始了这方面的研究，也取得了些喜人的进展。本文在前人研究基础上，首先概要的回顾了三维显示的发展史。接下来介绍了本文研究所需要的背景知识：包括人眼立体视觉基本机理，三维显示技术原理和分类。在人眼立体视觉基本机理中分单目感知深度和双目视差感知深度两类介绍。在三维显示技术原理和分类中按照眼镜式三维显示技术、裸眼三维显示技术、广义三维显示技术的顺序详细总结了领域内现行有效的三维显示技术原理及分类。
其次，全面的研究总结了现阶段产业领域内三维显示信息重建技术研究现状和所面临的问题。指出了三维显示信息重建技术的现实意义。基于对比分类的方法明确提出了三维显示信息重建（二维转三维）技术在全部的三维显示视频获取方法中的地位及意义。介绍了深度图的概念，详细描述了基于深度图的三维图像渲染技术（DIBR）。并站在二维转三维技术实际需要的角度，分析了二维转三维所需要的视频处理工具及研究现状。其中包括图像边缘检测算法、图像分割算法、模式识别、视频跟踪等。
遵循基于深度图渲染三维图像的逻辑，本文第三部分展开了探索工作，提出了套二维图像转换三维图像的视频处理系统。首先对图像进行预处理，包括二维图像获取、双边滤波。实验证明，本文应用双边滤波的方法对二维图像进行预处理有效的降低了二维转三维步骤的错误率。接下来，我们使用K-means聚类算法对预处理过后的图像进行分类，从而得到前景背景分离的等待赋予深度的图像。为了更准确的对经过聚类算法处理后的图像像素赋予深度，我们提出了基于经验性的图像布局模型，用于对图像中各目标区别性的做出深度赋值。实验证明，所提方式探索了种图像二维转三维的可行性方法，并为之后的研究奠定了定的理论基础。
我们还提出了种具有良好交互操作性的、半自动的基于二维视频获取三维视频关键信息的系统，在系统中，提出了基于目标跟踪算法完成非关键帧的深度图自动生成算法。系统可用于生成三维视频所需的深度信息。首先将视频提取关键帧，对关键帧进行基于懒惰抠图(lazy snapping)算法的图像分割。之后交互的将关键帧的主要目标进行标记，标记目标的深度信息随之赋值。对于非关键帧，根据关键帧的深度图，使用我们所提出的基于目标跟踪的非关键帧图像深度自动生成算法自动化的生成。最后，二维视频序列所对应的深度图像序列全部生成。我们在章节末尾提出了种二维转三维的系统框架。实验表明，我们提出的基于目标跟踪的非关键帧图像深度自动生成算法处理结果正确，能够生成较好的二维图像对应的深度图。
我们在研究二维转三维算法及系统的同时，考虑到目前三维显示产业尚属推广阶段，研究并提出了全面的立体电视图像质量测试方法。鉴于目前产业发展阶段实际需要，主要针对眼镜式三维显示提出平板立体电视机及平板立体显示器的立体图像质量的测量条件和测量方法。我们从工作条件、结果的表示、环境条件、电源、稳定时间、测试场地、测量位置、信号格式、测试信号、测量点和测量项目、测试仪器、标准测试状态等方面对立体电视图像质量的测试要求做出了全面的研究与规定。并提出了标准的测量方法用于参考。研究成果已经形成行业标准文本。
此外，我们基于测量不确定度的概念，对该领域内公认的能够产生接近标准的视频信号的广播电视测试信号发生器（SFU）进行了关于机顶盒电平指标测试的测量不确定度研究。提出了广播电视测试信号发生器的A类、B类测量不确定度评定方法。所提出的评价方法及实验所得结果可作为立体电视图像质量评价的测量不确定度评估依据。
最后结合产业应用实际，为了适应产业发展需求，提出了家庭网络系统体系结构和参考模型。适用于有三维显示及高清互动诉求的家庭或类似的室内场所的网络构建。并提出了种基于家庭内部电力线载波的网络融合解决方案。相关成果已形成国家标准报批。
The world we live in is a real, three-dimensional (3D) space. From ancientpainting recording image around or in mind, to the birth of a camera and videotape recorder, people never stopped pursuing more vivid and lively record ofthe world. When "Avatar" shock up the notion of traditional2-D images,3-Ddisplay became a household name and a new popular pursuit in the displayarea.
After enjoying the stunning visual shock of3-D images at the beginningof the21st century, people are eager to get more. However, large scale use of3-D display is still a challenge by now. Scarcity of3-D film sources is the mostimportant reason. The high-precision3-D camera can shoot any scene and usedfor3-D film and television production, but it is hard to widely spread due tohigh cost and long production cycle. At the same time, facing abundant andeasy making2-D images and videos, people also want to relive the samecontent under the3D shock effect. Therefore, the technology of3-Dinformation reconstruction came out.
The3-D display information reconstruction technology, i.e.2D-3Dconversion, is to convert2-D images or videos to acceptable3-D display ofimages and video through software algorithm. In the conversion process, thedepth of the image sequence (i.e."depth map") will be used. Depth map isinformation gap between2-D display and3-D display. When adding depth map,a2-D image will be able to convert to3-D image by using renderingtechnology based on depth (DIBR-depth image based rendering).Theoretically,this is a practical approach to breakthrough the bottleneck of3D industrydevelopment–lack of sources.
Related research started since the very beginning of21th century. Thereare also many encouraging research progress in this field. This paper, inChapter1, reviews the previous research of3-D technology, then introducesbackground knowledge of the research methods in our work, included basicprinciple of human eyes vision, principle and classification of3D displaytechnology. There are single eye depth perception and binocular parallax depth perception. We make a detailed analysis from three aspects, glassed typed3-Ddisplay, naked eyes typed3-D display and generalized3-D display；
In Chapter2, this paper summarizes current research status of3-D displayinformation reconstruction and industry problems at this stage；meanwhile,points out the important status and realistic significance of3-D displayinformation reconstruction techniques in whole3-D video capture process.This chapter introduces concept of depth map, describes3-D image renderingtechniques based on depth map (DI BR) in detail, and analyzes current videoprocessing tools and research status in2D-3D conversion, including imageedge detection algorithm, image segmentation algorithms, pattern recognitionand video tracking.
Following the logic of depth map based3-D rendering, Chapter3describeour exploration of a new2D-3D conversion system. The first step ispre-processing, including2-D image acquisition and bilateral filtering.Experiments show that bilateral filtering method we use in this paper for2-Dpreprocessing effectively lowered the error rate in2D-3D conversion. Afterthat, we classify objects in the image which has been pro-processed usingk-means clustering algorithm, and then image which foreground andbackground is divided and waiting for assigning depth value would be gotten.In order to assign depth value to the image more accurately, we propose layoutmodel of image which has been processed using k-means clustering algorithm.Experiment results shows that the method we proposed has explored anavailable2D to3D method, and laid the groundwork for future research.
We also propose a semiautomatic, interoperability system through whichkey information of3D video from2D video can be captured. In the system,automatic generation method of non-key frames depth map base on objecttracking algorithm has been proposed. The system can be used to generatedepth information which generation of3D video required. First, get key framefrom video, do image segmentation based lazy snapping algorithm on keyframe, then label main object in key frame interactively, depth value will begiven after that. For non-key frames, according to depth map of key frames, weuse generation method of non-key frames depth map base on object trackingalgorithm which we proposed to generate depth map of non-key frame automatically. Finally, depth image sequence which corresponds to2D videosequence has been generated. We propose2D to3D system framework at theend of this chapter. The experimental results show that the generation methodof non-key frames depth map base on object tracking algorithm which wepropose can get correct result, depth map generation using this algorithm hasgood performance.
While making deep research of2D to3D algorithms and system,considering3D display industry is still at the stage of promotion, we proposecomprehensive method of measurement for the image quality of3DTV. In viewof actual needs of this industrial development stage, we propose measurementconditions and measurement method for quality of flat panel stereo TV and flatpanel stereo terminal in the type of glassed3D display. We makecomprehensive research and rule on image quality of3DTV measurementrequirement. Include following aspects, working conditions, environmentalpresentation, power, stable duration, measurement site, measurement position,format of test signal, measurement points and measurement points,measurement instruments, standard test status. And we raise reference standardmeasurement methods. Research results have formed the industry standardtext.
In addition, based on the concept of measurement uncertainty, this paperstudies the measurement uncertainty of set-top box’s electrical level test byusing SFU (Single Family Unit)-one kind of broadcast test system instrumentwhich is widely considered can generate more-or-less standard video signals.We propose evaluation methods aim at A-class and B-class measurementuncertainty respective. The evaluation methods and the experimental result canbe applied to evaluate image quality of3-D television.
At last, we combined with the actual industry application experience,designs a family network system architecture and reference model which ismore adaptable in real family network construction scenarios in demanding of3-D display and high definition interactions. We also proposed a networkconvergence solution based on indoor Power-Line Carrier (PLC) network,which is already in approval process for national standards.
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