摘要
随着深度学习和3D传感技术的快速发展,点云分类已在智能分级等领域得到了广泛的应用。为了更好地推进点云分类技术的研究与应用,利用管道体系结构对相关方法的研究进展进行全面而系统的梳理、分析和总结。首先,根据点云数据处理方式的不同,将现有的点云分类方法归纳为间接基于点云的方法和直接基于点云的方法。然后,着重介绍了具有代表性的方法和最新研究成果,同时比较分析了主要方法的核心思想、优缺点、适用范围、应用场景以及实验结果。最后,从四个方面对点云分类的未来发展以及研究方向进行了展望,结果表明,将间接和直接点云的方法进行2D-3D特征融合是未来的一个重要发展方向。
With the rapid development of deep learning and 3D sensing technology,point cloud classification has been widely used in intelligent classification and other fields.In order to better promote the research and application of point cloud classification technology,this paper combed,analyzed and summarized the research progress of related methods systematically by using pipeline architecture.Firstly,according to the different point cloud data processing methods,it analyzed and summarized the existing point cloud classification methods into indirect point cloud based methods and direct point cloud based methods.Then,it introduced the representative methods and the latest research,compared and analyzed the core ideas,advantages and disadvantages,scope of application,application scenarios and experimental results of the main methods.Finally,it prospected the future development and research direction of point cloud classification from four aspects.The results show that 2D-3D feature fusion of indirect and direct point cloud methods is an important development direction in the future.
作者
魏天琪
郑雄胜
Wei Tianqi;Zheng Xiongsheng(Zhejiang Ocean University,Zhoushan Zhejiang 316022,China)
出处
《计算机应用研究》
CSCD
北大核心
2022年第5期1289-1296,共8页
Application Research of Computers
基金
舟山市科技计划项目(2021C21005)
浙江省科技厅尖兵领雁计划项目(2022C02001)。
关键词
计算机视觉
智能分级
深度学习
三维点云
点云分类
computer vision
intelligent classification
deep learning
3D point cloud
point cloud classification
