GFFS:三维点云重力-力特征实时分割

Chunhao Shi, Chunyang Wang, Xuelian Liu, Boyang Xiao, Shaoyu Sun, Guan Xi, Wenqian Qiu
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引用次数: 0

摘要

点云分割是自动驾驶汽车的一项重要技术。由于道路环境的多样性和复杂性,基于点云的实例分割是一项具有挑战性的任务。针对这一挑战,提出了一种三维点云的重力特征分割方法。首先将点划分为多个区域,然后根据点云的大小和密度设置每个区域对应的球邻域半径,然后计算每个球邻域空间与区域重心之间的引力。GFFS通过分析重力的大小和连续性,对点云场景中各类物体进行实例分割。最后,通过实验验证了该算法的优越性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GFFS: Gravitational-Force Feature Real Time Segmentation of 3D Point Cloud
Segmentation of point cloud is a momentous technology for autonomous vehicles. Due to the diversity and complexity of road environment, instance segmentation based on point cloud is a challenging task. Addressing this challenge, a gravitational-force feature segmentation of 3D point cloud (GFFS) is proposed. Firstly it divides the point into areas, secondly it sets the radius of the spherical neighborhood corresponding to each area based on the size and density of point cloud, thirdly it calculates the gravitational forces between the space of each spherical neighborhood and the barycenter of the area. GFFS performs instance segmentation of all kinds of objects in point cloud scene by analyzing the magnitude and continuity of gravitational forces. Finally, the superiority and effectiveness of the algorithm are verified by experiments.
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