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3D object to 2D image invariance technology for visualization problems

机译:用于可视化问题的3D对象到2D图像不变性技术

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In this paper, we describe applications of a startling recent approach to image recognition and understanding, explore some of the benefits, and list potential visualization applications of this technology. The basis of this work consists of a mathematical formalism which allows one to associate a particular three-dimensional representation of an object or landscape with any of its two-dimensional image views. In contrast to other work in this area, these techniques do not require knowledge of camera parameters (focal length, image scale, etc.) and require only a single image of a given scene. These methods do not rely on trigonometry or off-board information sources (e.g. GPS). They work from image features which are general and common (i.e. lines and points). These properties make the technology particularly desirable for applications such as navigation, cueing, targeting, and image "patching". We will begin with an overview of the geometric theory. We will then discuss what these discoveries allow us to do. Finally we will point to some specific capabilities shortfalls in the military today to which this work could be addressed.
机译:在本文中,我们描述了一种令人震惊的最新方法在图像识别和理解中的应用,探索了一些好处,并列出了该技术的潜在可视化应用。这项工作的基础是一种数学形式主义,它使人们可以将物体或风景的特定三维表示与其二维图像视图中的任何一个相关联。与该领域的其他工作相比,这些技术不需要了解相机参数(焦距,图像比例等),并且只需要给定场景的单个图像即可。这些方法不依赖于三角函数或外部信息源(例如GPS)。它们从通用的图像特征(即线和点)开始工作。这些特性使该技术特别适合诸如导航,提示,瞄准和图像“修补”之类的应用。我们将从几何理论的概述开始。然后,我们将讨论这些发现允许我们做什么。最后,我们将指出可以解决这项工作的当今军事上某些特定的能力不足。

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