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Handling Motion-Blur in 3D Tracking and Rendering for Augmented Reality

机译:为增强现实处理3D跟踪和渲染中的运动模糊

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The contribution of this paper is two-fold. First, we show how to extend the ESM algorithm to handle motion blur in 3D object tracking. ESM is a powerful algorithm for template matching-based tracking, but it can fail under motion blur. We introduce an image formation model that explicitly consider the possibility of blur, and shows its results in a generalization of the original ESM algorithm. This allows to converge faster, more accurately and more robustly even under large amount of blur. Our second contribution is an efficient method for rendering the virtual objects under the estimated motion blur. It renders two images of the object under 3D perspective, and warps them to create many intermediate images. By fusing these images we obtain a final image for the virtual objects blurred consistently with the captured image. Because warping is much faster than 3D rendering, we can create realistically blurred images at a very low computational cost.
机译:本文的贡献是双重的。首先,我们展示如何扩展ESM算法以处理3D对象跟踪中的运动模糊。 ESM是用于基于模板匹配的跟踪的强大算法,但在运动模糊下可能会失败。我们介绍了一种图像形成模型,该模型明确考虑了模糊的可能性,并在原始ESM算法的推广中展示了其结果。即使在大量模糊情况下,这也可以更快,更准确和更可靠地收敛。我们的第二个贡献是一种在估计的运动模糊下渲染虚拟对象的有效方法。它在3D透视下渲染对象的两个图像,并将它们扭曲以创建许多中间图像。通过融合这些图像,我们获得了与捕获的图像一致模糊的虚拟对象的最终图像。因为扭曲比3D渲染快得多,所以我们可以以非常低的计算成本来创建逼真的模糊图像。

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