GPU-based supervoxel segmentation for 3D point clouds

doi:10.1016/j.cagd.2022.102080

科研成果详情

题名	GPU-based supervoxel segmentation for 3D point clouds
作者	Dong，Xiao 1; Xiao，Yanyang 2; Chen，Zhonggui 1; Yao，Junfeng 3; Guo，Xiaohu 4
发表日期	2022-02-01
发表期刊	Computer Aided Geometric Design
ISSN/eISSN	0167-8396
卷号	93
摘要	Point cloud processing has received more attention in recent years. Due to the huge amount of data, using supervoxels to pre-segment the points can improve the performance of point cloud processing tasks. There are some supervoxel algorithms generating high-quality results, but their low efficiency hinders the wide application in point cloud processing tasks. In this paper, we try to strike a good balance between the quality and efficiency of point cloud over-segmentation. We propose an algorithm suitable for GPU acceleration, which can generate supervoxel with high efficiency. The algorithm is a seed-based segmentation method, and we carefully design two stages: the clustering stage and optimization stage, each of which can be executed in parallel on the GPU. In the first stage, the algorithm generates an initial segmentation based on well designed energy functions, and the second stage further improves the result by minimizing the segmentation energy. Our method generates good segmentation results and achieves the fastest processing speed compared with the existing methods. We evaluate the supervoxels on three public datasets. Experiments show that our algorithm can generate high-quality segmentation for various point cloud data with high efficiency, which is important for advancing the application of point cloud supervoxels in subsequent processing.
关键词	GPU computation Point clouds Supervoxel segmentation
DOI	10.1016/j.cagd.2022.102080
URL	查看来源
语种	英语English
Scopus入藏号	2-s2.0-85126880148
引用统计
文献类型	期刊论文
条目标识符	https://repository.uic.edu.cn/handle/39GCC9TT/13848
专题	个人在本单位外知识产出
通讯作者	Chen，Zhonggui
作者单位	1.School of Informatics,Xiamen University,Xiamen,Fujian,361005,China 2.School of Information Engineering,Nanchang University,Nanchang,Jiangxi,330031,China 3.School of Film,Xiamen University,Xiamen,Fujian,361005,China 4.Department of Computer Science,University of Texas at Dallas,Dallas,75083,United States
推荐引用方式 GB/T 7714	Dong，Xiao,Xiao，Yanyang,Chen，Zhongguiet al. GPU-based supervoxel segmentation for 3D point clouds[J]. Computer Aided Geometric Design, 2022, 93.
APA	Dong，Xiao, Xiao，Yanyang, Chen，Zhonggui, Yao，Junfeng, & Guo，Xiaohu. (2022). GPU-based supervoxel segmentation for 3D point clouds. Computer Aided Geometric Design, 93.
MLA	Dong，Xiao,et al."GPU-based supervoxel segmentation for 3D point clouds". Computer Aided Geometric Design 93(2022).