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Reliable 3D video streaming considering region of interest

机译:考虑感兴趣区域的可靠3D视频流

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摘要

3D video applications are growing more common as communication technology becomes more predominant nowadays. With such increasing demand for the 3D multimedia services in either the wired or wireless networks, robust methods of video streaming will be introduced to show more favorable efficiency outcomes since packet failure is an integral characteristic of communication networks.This paper aims to introduce a new reliable method of stereoscopic video streaming based on multiple description coding (MDC) strategy. The proposed multiple description coding generates four 3D video descriptions considering the interesting objects contained in the scene. To be able to find the interesting objects in the scene, we use two metrics from the second-order statistics of the depth map image in a block-wise manner. Having detected the objects, the proposed multiple description coding algorithm generates the descriptions for the color video using a nonidentical decimation method with respect to the identified objects. To show how much reliable the proposed MDC method is, this article assumes that due to the unreliable communication channel, only one description, among four encoded descriptions, is delivered to the receiver successfully. Therefore, the receiver needs to estimate the missed descriptions’ data from the available description. Since the human eye is more sensitive to objects than it is to pixels, the proposed method provides a better visual performance in view of its subjective assessment. Although, the objective test results verify the fact that the proposed method provides an improved performance than the Polyphase SubSampling (PSS) multiple description coding and our previous work using pixel variation. Regarding the depth map image, the proposed method generates the multiple descriptions according to the pixel prediction difficulty level. The considerable improvement achieved by the proposed method is shown with the peak signal-to-noise ratio (PSNR) and Structural SIMilarity (SSIM) simulation result.
机译:如今,随着通信技术变得越来越流行,3D视频应用程序变得越来越普遍。随着对有线或无线网络中3D多媒体服务的需求不断增长,由于数据包故障是通信网络不可或缺的特性,因此将引入鲁棒的视频流方法以显示出更好的效率结果。本文旨在介绍一种新的可靠方法。多描述编码(MDC)策略的立体视频流传输方法。考虑到场景中包含的有趣对象,建议的多描述编码生成了四个3D视频描述。为了能够找到场景中有趣的对象,我们以块方式使用深度图图像的二阶统计量中的两个度量。在检测到对象之后,所提出的多描述编码算法使用针对所标识的对象的非完全抽取方法来生成彩色视频的描述。为了显示所提出的MDC方法的可靠性,本文假设由于通信通道不可靠,在四个编码描述中,只有一个描述已成功传递给接收器。因此,接收者需要从可用描述中估算错过的描述数据。由于人眼对物体比对像素更敏感,因此考虑到其主观评估,该方法可提供更好的视觉性能。虽然,客观测试结果证明了以下事实:与多相子采样(PSS)多描述编码和我们以前使用像素变化的工作相比,该方法提供了更高的性能。对于深度图图像,所提出的方法根据像素预测难度级别生成多个描述。峰值信噪比(PSNR)和结构相似度(SSIM)仿真结果显示了该方法所取得的显着改进。

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