Monocular, Real-Time Surface Reconstruction Using Dynamic Level of Detail

J. Zienkiewicz, Akis Tsiotsios, A. Davison, Stefan Leutenegger
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引用次数: 30

Abstract

We present a scalable, real-time capable method for robust surface reconstruction that explicitly handles multiple scales. As a monocular camera browses a scene, our algorithm processes images as they arrive and incrementally builds a detailed surface model.While most of the existing reconstruction approaches rely on volumetric or point-cloud representations of the environment, we perform depth-map and colour fusion directly into a multi-resolution triangular mesh that can be adaptively tessellated using the concept of Dynamic Level of Detail. Our method relies on least-squares optimisation, which enables a probabilistically sound and principled formulation of the fusion algorithm.We demonstrate that our method is capable of obtaining high quality, close-up reconstruction, as well as capturing overall scene geometry, while being memory and computationally efficient.
使用动态细节水平的单目实时表面重建
我们提出了一种可扩展的、实时的鲁棒表面重建方法,可以明确地处理多个尺度。当单目相机浏览场景时,我们的算法在图像到达时进行处理,并逐步建立详细的表面模型。虽然大多数现有的重建方法依赖于环境的体积或点云表示,但我们直接将深度图和颜色融合到一个多分辨率三角形网格中,该网格可以使用动态细节水平的概念自适应地镶嵌。我们的方法依赖于最小二乘优化,这使得融合算法的概率健全和原则性的公式。我们证明了我们的方法能够获得高质量的近距离重建,以及捕获整体场景几何,同时具有内存和计算效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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