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Automatic Ground Surface Reconstruction from mobile laser systems for driving simulation engines

机译:来自移动激光系统的自动地面重建,用于驱动仿真引擎

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摘要

Driving simulation engines represent a cost effective solution for vehicle development, being employed for performing feasibility studies and tests failure and for assessing new functionalities. Nevertheless, they require geometrically accurate and realistic three-dimensional (3D) models in order to allow driver training. This paper presents the Automatic Ground Surface Reconstruction method, a framework that exploits 3D data acquired by Mobile Laser Scanning systems. They are particularly attractive due to their fast acquisition at the terrestrial level. Nevertheless, such a mobile acquisition introduces several constraints for the existing 3D surface reconstruction algorithms. The proposed surface modeling framework produces a regular surface and recovers sharp depth features within a scalable and detail-preserving framework. Experimental results on real data acquired in urban environments allow us to conclude on the effectiveness of the proposed method.
机译:驾驶仿真引擎代表了一种用于车辆开发的经济高效的解决方案,被用于进行可行性研究和测试故障以及评估新功能。但是,他们需要几何上精确且逼真的三维(3D)模型,以便进行驾驶员培训。本文介绍了自动地面重建方法,该方法利用了移动激光扫描系统获取的3D数据。由于它们在地面上的快速获取,它们特别有吸引力。然而,这样的移动获取对现有的3D表面重建算法引入了一些约束。拟议的表面建模框架可生成规则的表面并在可扩展且保留细节的框架内恢复尖锐的深度特征。在城市环境中获取的真实数据的实验结果使我们能够对所提方法的有效性做出结论。

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