基于kinect v2的动态场景实时多视角体重建

Andrej Satnik, E. Izquierdo
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引用次数: 3

摘要

为了获得高质量的三维内容,在显示和处理实时三维数据时,一个关键的挑战是生成和后处理算法的效率。相比之下,我们的方法侧重于使用高效低成本的硬件设置生成和处理体积数据。体积数据的获取是通过将多个Kinect v2扫描仪连接到一台PC上进行的,随后使用平面模式进行校准。这个过程绝不是微不足道的,需要设计良好的算法来快速处理和快速渲染体积数据。这可以通过融合有效的滤波方法,如加权中值滤波(WM)、半径离群值去除(ROR)和基于拉普拉斯的平滑算法来实现。在这种情况下,我们通过感知几个场景来证明我们的技术的鲁棒性和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
REAL-TIME MULTI-VIEW VOLUMETRIC RECONSTRUCTION OF DYNAMIC SCENES USING KINECT V2
A key challenge when displaying and processing sensed real-time 3D data is efficiency of generating and post-processing algorithms in order to acquire high quality 3D content. In contrast, our approach focuses on volumetric generation and processing volumetric data using an efficient low-cost hardware setting. Acquisition of volumetric data is performed by connecting several Kinect v2 scanners to a single PC that are subsequently calibrated using planar pattern. This process is by no means trivial and requires well designed algorithms for fast processing and quick rendering of volumetric data. This can be achieved by fusing efficient filtering methods such as Weighted median filter (WM), Radius outlier removal (ROR) and Laplace-based smoothing algorithm. In this context, we demonstrate the robustness and efficiency of our technique by sensing several scenes.
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