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Synchronizing real and predicted synthetic video imagery for localization of a robot to a 3D environment

机译:同步真实和预测的合成视频图像,以将机器人定位到3D环境

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A mobile robot moving in an environment in which there are other moving objects and active agents, some of which may represent threats and some of which may represent collaborators, needs to be able to reason about the potential future behaviors of those objects and agents. In previous work, we presented an approach to tracking targets with complex behavior, leveraging a 3D simulation engine to generate predicted imagery and comparing that against real imagery. We introduced an approach to compare real and simulated imagery using an affine image transformation that maps the real scene to the synthetic scene in a robust fashion.rnIn this paper, we present an approach to continually synchronize the real and synthetic video by mapping the affine transformation yielded by the real/synthetic image comparison to a new pose for the synthetic camera. We show a series of results for pairs of real and synthetic scenes containing objects including similar and different scenes.
机译:在具有其他移动对象和活动代理(其中一些可能表示威胁而某些可能表示协作者)的环境中移动的移动机器人需要能够推理出这些对象和代理的潜在未来行为。在先前的工作中,我们提出了一种跟踪具有复杂行为的目标的方法,利用3D仿真引擎生成预测的图像并将其与真实图像进行比较。我们介绍了一种使用仿射图像变换比较真实图像和模拟图像的方法,该方法将真实场景映射到合成场景。本白皮书中,我们提出了一种通过映射仿射变换来连续同步真实和合成视频的方法通过将实际/合成图像与合成相机的新姿势进行比较而得出。对于包含对象(包括相似和不同场景)的真实和合成场景对,我们显示了一系列结果。

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