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Locating and Tracking Objects by Efficient Comparison of Real and Predicted Synthetic Video Imagery

机译:通过有效比较实际和预测的合成视频图像来定位和跟踪对象

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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 this paper we present an approach to tracking targets with complex behavior, leveraging a 3D simulation engine to generate predicted imagery and comparing that against real imagery. We introduce an approach to compare real and simulated imagery and present results using this approach to locate and track objects with complex behaviors.rnIn this approach, the salient points in real and imaged images are identified and an affine image transformation that maps the real scene to the synthetic scene is generated. An image difference operation is developed that ensures that the matched points in both images produce a zero difference. In this way, synchronization differences are reduced and content differences enhanced. A number of image pairs are processed and presented to illustrate the approach.
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。在本文中,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。我们介绍了一种比较真实图像和模拟图像的方法,并使用此方法来定位和跟踪具有复杂行为的对象.rn这种方法可以识别真实图像和成像图像中的显着点,并通过仿射图像变换将真实场景映射到合成场景已生成。开发了图像差异运算,以确保两个图像中的匹配点产生零差异。以此方式,减少了同步差异并且增强了内容差异。处理并显示了许多图像对以说明该方法。

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