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Cubic-Panorama Image Dataset Analysis for Storage and Transmission

机译:用于存储和传输的立方全景图像数据集分析

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In this paper we address the problem of disparity estimation required for free navigation in acquired cubicpanorama image datasets. A client server based scheme is assumed and a remote user is assumed to seek information at each navigation step. The initial compression of such image datasets for storage as well as the transmission of the required data is addressed in this work. Regarding the compression of such data for storage, a fast method that uses properties of the epipolar geometry together with the cubic format of panoramas is used to estimate disparity vectors efficiently. Assuming the use of B pictures, the concept of forward and backward prediction is addressed. Regarding the transmission stage, a new disparity vector transcoding-like scheme is introduced and a frame conversion scenario is addressed. Details on how to pick the best vector among candidate disparity vectors is explained. In all the above mentioned cases, results are compared both visually through error images as well as using the objective measure of Peak Signal to Noise Ratio (PSNR) versus time.
机译:在本文中,我们解决了获取的CubicPanorama图像数据集中自由导航所需的差异估计问题。假设基于客户端服务器的方案,并且假设远程用户在每个导航步骤中寻求信息。在该工作中解决了这种图像数据集的初始压缩以及所需数据的传输。关于这种存储数据的压缩,使用与全景的立方格式一起使用eMipolar几何的特性的快速方法用于有效地估计视差矢量。假设使用B图片,解决了向前和向后预测的概念。关于传输级,引入了新的视差矢量代码转换等方案,并且寻址帧转换方案。有关如何选择候选差距向量中最佳载体的详细信息。在所有上述情况下,通过误差图像以及使用峰值信号的客观度量与噪声比(PSNR)与时间相比,将结果进行比较。

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