This article describes novel approaches to quickly estimate planar surfaces from RGBD sensor data. The approach manipulates the standard algebraic fitting equations into a form that allows many of the needed regression variables to be computed directly from the camera calibration information. As such, much of the computational burden required by a standard algebraic surface fit can be pre-computed. This provides a significant time and resource savings, especially when many surface fits are being performed which is often the case when RGBD point-cloud data is being analyzed for normal estimation, curvature estimation, polygonization or 3D segmentation applications. Using an integral image implementation, the proposed approaches show a significant increase in performance compared to the standard algebraic fitting approaches.
翻译:本篇文章描述了快速估计RGBD传感器数据平面的新方法。 该方法将标准的代数搭配方程式操作成一种形式,使许多所需的回归变量能够直接从相机校准信息中计算出来。 因此,标准代数表需要的计算负担大都可预先计算出来。 这提供了相当的时间和资源节约,特别是当许多表面装配正在进行时,而当正在对RGBD点柱数据进行分析以进行正常估计、曲线估计、多角化或3D分化应用时,情况往往是这样。 采用集成图像执行方法,建议的方法显示,与标准的代数装配方法相比,性能显著提高。