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首页> 外文期刊>Journal of supercomputing >Real-time 3D reconstruction method using massive multi-sensor data analysis and fusion
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Real-time 3D reconstruction method using massive multi-sensor data analysis and fusion

机译:使用大规模多传感器数据分析和融合的实时3D重建方法

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摘要

This paper proposes a method to reconstruct three-dimensional (3D) objects using real-time fusion and analysis of multiple sensor data. This paper attempts to create a realistic 3D visualization with which a remote pilot can intuitively control a remote unmanned robot by utilizing the characteristics of massive sensor data. The 3D reconstruction system proposed in this paper is comprised of 3D and two-dimensional (2D) data segmentation method, a 3D reconstruction method applied to each object, and a projective texture mapping method. Specifically, we propose applying both a 2D region extraction method and a 3D mesh modeling method to each object. The proposed schemes are implemented as a real-time application to verify real-time performance. This paper proves that 3D meshes can be modeled in real time by using the proposed method. The proposed method allows the remote control of a robot for real-time 3D rendering of remote scenes, which is essential for various tasks in areas that cannot be easily accessed by humans.
机译:本文提出了一种使用多次融合和多个传感器数据分析来重建三维(3D)对象的方法。本文试图通过利用大规模传感器数据的特性,创建一个现实的3D可视化,其中远程导频可以直观地直观地控制远程无人机器人。本文提出的3D重建系统由3D和二维(2D)数据分割方法组成,应用于每个对象的3D重建方法,以及投影纹理映射方法。具体地,我们建议将2D区域提取方法和3D网格建模方法应用于每个对象。建议的方案被实施为验证实时性能的实时应用程序。本文证明了通过使用所提出的方法可以实时建模3D网格。所提出的方法允许远程控制机器人进行远程场景的实时3D渲染,这对于人类不能容易地访问的区域中的各种任务至关重要。

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