以交互速率可视化非常大的图像数据集

Frank Edughom Ekpar, H. Hase, M. Yoneda
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引用次数: 2

摘要

本文提出了一种基于按需加载和动态视图预测的超大图像数据集实时可视化系统。我们采用鲁棒的图像表示方案来实现高效的自适应渲染,并引入快速透视视图生成模块来扩展系统对全景图像的适用性。我们通过将该系统应用于不需要透视校正的图像和需要透视视图生成的非常大的全景数据集来证明该系统的有效性。此外,我们对系统进行了扩展和推广,以实现广泛的应用。在广泛的应用中,该系统允许在普通个人计算机上对非常大的全景和非全景图像数据集进行平滑、实时的交互式导航,而无需使用专门的硬件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visualizing Very Large Image Data Sets At Interactive Rates
This paper presents a system for real-time visualization of very large image data sets using ondemand loading and dynamic view prediction. We use a robust image representation scheme for efficient adaptive rendering and introduce a fast perspective view generation module to extend the applicability of the system to panoramic images. We demonstrate the effectiveness of the system by applying it both to imagery that does not require perspective correction and to very large panoramic data sets requiring perspective view generation. Furthermore, we extend and generalize the system to enable a wide range of applications. In a broad set of applications, the system permits smooth, real-time interactive navigation of very large panoramic and non-panoramic image data sets on average personal computers without the use of specialized hardware.
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