Recently, the popularity of 3D content is on the rise because of its immersive experience to view- ers. While demands for 3D contents and 3D technologies increase, only a few copyright protection methods for 3D conten...Recently, the popularity of 3D content is on the rise because of its immersive experience to view- ers. While demands for 3D contents and 3D technologies increase, only a few copyright protection methods for 3D contents have been proposed. The simplest infringement is the illegal distribution of the single 2D image from 3D content. The leaked image is still valuable as 2D content and the leakage can be occurred in DIBR system. To detect the leaked image, we focus on the hole-filled region which is caused by the hole-filling procedure mandatory in DIBR system. To estimate the hole-filled regions, two different procedures are conducted to extract edges and to estimate 3D warping traces, respectively. After that, the hole-filled regions are estimated and the left-right-eye image discrimination (LR discrimination) is also conducted. Experimental results demonstrate the effectiveness of the proposed method using quantitative measures.展开更多
六自由度(Six Degree of Freedom,6DoF)视频系统允许用户从全方位、以任意视角身临其境地体验场景,是沉浸式视频技术的发展方向。根据6DoF视频系统中用户观看位置的变化,对多视点彩色与深度视频的码率分配是高质量场景生成的关键。本文...六自由度(Six Degree of Freedom,6DoF)视频系统允许用户从全方位、以任意视角身临其境地体验场景,是沉浸式视频技术的发展方向。根据6DoF视频系统中用户观看位置的变化,对多视点彩色与深度视频的码率分配是高质量场景生成的关键。本文从虚拟视点的失真出发,提出一种基于虚拟视点质量预测(Quality prediction model of virtual view,QPMVV)模型的视点级码率分配方法。首先理论分析了彩色和深度视频编码失真和虚拟视点失真的关系,然后通过实验统计分析了虚拟视点质量与彩色和深度视频编码量化参数的关系,建立了多视点彩色和深度视频的QPMVV模型,最后推导出多视点彩色和深度视频的相关视点的码率分配比例。实验表明,与平均分配的方法相比,本文码率分配方法能显著提升虚拟视点的主观和客观质量。虚拟视点越偏离中心位置,质量改善越明显。展开更多
Depth-image-based rendering(DIBR) is widely used in 3 DTV, free-viewpoint video, and interactive 3 D graphics applications. Typically, synthetic images generated by DIBR-based systems incorporate various distortions, ...Depth-image-based rendering(DIBR) is widely used in 3 DTV, free-viewpoint video, and interactive 3 D graphics applications. Typically, synthetic images generated by DIBR-based systems incorporate various distortions, particularly geometric distortions induced by object dis-occlusion. Ensuring the quality of synthetic images is critical to maintaining adequate system service. However, traditional 2 D image quality metrics are ineffective for evaluating synthetic images as they are not sensitive to geometric distortion. In this paper, we propose a novel no-reference image quality assessment method for synthetic images based on convolutional neural networks, introducing local image saliency as prediction weights. Due to the lack of existing training data, we construct a new DIBR synthetic image dataset as part of our contribution. Experiments were conducted on both the public benchmark IRCCyN/IVC DIBR image dataset and our own dataset. Results demonstrate that our proposed metric outperforms traditional 2 D image quality metrics and state-of-the-art DIBR-related metrics.展开更多
针对基于深度图像绘制技术(depth-image based rendering,DIBR)中产生的空洞问题,为提高虚拟视点质量,提出一种基于深度图像绘制技术的Criminisi改进算法。对优先级进行改进,加入指数形式的置信度项和新的数据项,加强对细节部分的填补;...针对基于深度图像绘制技术(depth-image based rendering,DIBR)中产生的空洞问题,为提高虚拟视点质量,提出一种基于深度图像绘制技术的Criminisi改进算法。对优先级进行改进,加入指数形式的置信度项和新的数据项,加强对细节部分的填补;在搜索最佳匹配块时,采用新的颜色匹配因子,添加梯度因子,结合深度因子,对映射后的纹理图和相对应的深度图进行搜索匹配。实验结果表明,相较传统空洞填补算法,改进算法在主观图像质量与客观峰值信噪比(peak signal to noise ratio,PSNR)方面有所提高。展开更多
针对基于双向深度图像绘制技术(Double-sided Depth-Image Based Rendering,Double-sided DIBR)中产生的空洞、重采样、重叠问题,为提高虚拟图像的合成质量,提出一种改进的正反向映射技术。该技术主要有四点贡献。(1)提出一种深度差值...针对基于双向深度图像绘制技术(Double-sided Depth-Image Based Rendering,Double-sided DIBR)中产生的空洞、重采样、重叠问题,为提高虚拟图像的合成质量,提出一种改进的正反向映射技术。该技术主要有四点贡献。(1)提出一种深度差值估计法。(2)在3D-warping过程中使用改进的基于Z-buffer的OPFD算法,有效解决重采样和重叠问题。(3)对深度虚拟图像运用改进的基于背景空洞填补算法消除空洞。(4)改进反向映射过程,通过判断投影后的图像和辅助彩色参考图像被遮挡信息背景的一致性,选择不同的空洞填补算法填补彩色虚拟图像中的空洞,从而达到更好的填补效果。实验结果表明,改进技术在降低算法复杂度的同时,主观图像质量与客观峰值信噪比(Peak Signal to Noise Ratio,PSNR)以及结构相似(Structural SIMilarity,SSIM)都有所提高。展开更多
文摘Recently, the popularity of 3D content is on the rise because of its immersive experience to view- ers. While demands for 3D contents and 3D technologies increase, only a few copyright protection methods for 3D contents have been proposed. The simplest infringement is the illegal distribution of the single 2D image from 3D content. The leaked image is still valuable as 2D content and the leakage can be occurred in DIBR system. To detect the leaked image, we focus on the hole-filled region which is caused by the hole-filling procedure mandatory in DIBR system. To estimate the hole-filled regions, two different procedures are conducted to extract edges and to estimate 3D warping traces, respectively. After that, the hole-filled regions are estimated and the left-right-eye image discrimination (LR discrimination) is also conducted. Experimental results demonstrate the effectiveness of the proposed method using quantitative measures.
文摘六自由度(Six Degree of Freedom,6DoF)视频系统允许用户从全方位、以任意视角身临其境地体验场景,是沉浸式视频技术的发展方向。根据6DoF视频系统中用户观看位置的变化,对多视点彩色与深度视频的码率分配是高质量场景生成的关键。本文从虚拟视点的失真出发,提出一种基于虚拟视点质量预测(Quality prediction model of virtual view,QPMVV)模型的视点级码率分配方法。首先理论分析了彩色和深度视频编码失真和虚拟视点失真的关系,然后通过实验统计分析了虚拟视点质量与彩色和深度视频编码量化参数的关系,建立了多视点彩色和深度视频的QPMVV模型,最后推导出多视点彩色和深度视频的相关视点的码率分配比例。实验表明,与平均分配的方法相比,本文码率分配方法能显著提升虚拟视点的主观和客观质量。虚拟视点越偏离中心位置,质量改善越明显。
基金sponsored by the National Key R&D Program of China (No. 2017YFB1002702)the National Natural Science Foundation of China (Nos. 61572058, 61472363)
文摘Depth-image-based rendering(DIBR) is widely used in 3 DTV, free-viewpoint video, and interactive 3 D graphics applications. Typically, synthetic images generated by DIBR-based systems incorporate various distortions, particularly geometric distortions induced by object dis-occlusion. Ensuring the quality of synthetic images is critical to maintaining adequate system service. However, traditional 2 D image quality metrics are ineffective for evaluating synthetic images as they are not sensitive to geometric distortion. In this paper, we propose a novel no-reference image quality assessment method for synthetic images based on convolutional neural networks, introducing local image saliency as prediction weights. Due to the lack of existing training data, we construct a new DIBR synthetic image dataset as part of our contribution. Experiments were conducted on both the public benchmark IRCCyN/IVC DIBR image dataset and our own dataset. Results demonstrate that our proposed metric outperforms traditional 2 D image quality metrics and state-of-the-art DIBR-related metrics.
文摘提出了一种基于Kinect的实时深度提取算法和单纹理+深度的多视绘制方法。在采集端,使用Kinect提取场景纹理和深度,并针对Kinect输出深度图的空洞提出一种快速修复算法。在显示端,针对单纹理+深度的基于深度图像的绘制(DIBR,depth image based rendering)绘制产生的大空洞,采用一种基于背景估计和前景分割的绘制方法。实验结果表明,本文方法可实时提取质量良好的深度图,并有效修复了DIBR绘制过程中产生的大空洞,得到质量较好的多路虚拟视点图像。以所提出的深度获取和绘制算法为核心,实现了一种基于深度的立体视频系统,最终的虚拟视点交织立体显示的立体效果良好,进一步验证了本文算法的有效性。本文系统可用于实景的多视点立体视频录制与播放。
文摘针对基于深度图像绘制技术(depth-image based rendering,DIBR)中产生的空洞问题,为提高虚拟视点质量,提出一种基于深度图像绘制技术的Criminisi改进算法。对优先级进行改进,加入指数形式的置信度项和新的数据项,加强对细节部分的填补;在搜索最佳匹配块时,采用新的颜色匹配因子,添加梯度因子,结合深度因子,对映射后的纹理图和相对应的深度图进行搜索匹配。实验结果表明,相较传统空洞填补算法,改进算法在主观图像质量与客观峰值信噪比(peak signal to noise ratio,PSNR)方面有所提高。
文摘针对基于双向深度图像绘制技术(Double-sided Depth-Image Based Rendering,Double-sided DIBR)中产生的空洞、重采样、重叠问题,为提高虚拟图像的合成质量,提出一种改进的正反向映射技术。该技术主要有四点贡献。(1)提出一种深度差值估计法。(2)在3D-warping过程中使用改进的基于Z-buffer的OPFD算法,有效解决重采样和重叠问题。(3)对深度虚拟图像运用改进的基于背景空洞填补算法消除空洞。(4)改进反向映射过程,通过判断投影后的图像和辅助彩色参考图像被遮挡信息背景的一致性,选择不同的空洞填补算法填补彩色虚拟图像中的空洞,从而达到更好的填补效果。实验结果表明,改进技术在降低算法复杂度的同时,主观图像质量与客观峰值信噪比(Peak Signal to Noise Ratio,PSNR)以及结构相似(Structural SIMilarity,SSIM)都有所提高。
