计算机与现代化Issue(12)：24-29,6.DOI:10.3969/j.issn.1006-2475.2023.12.005
基于多阶段分形组合的点云补全算法
Point Cloud Completion Algorithm Based on Multi-stage Fractal Combination
摘要
Abstract
Point cloud is a common representation of 3D objects.However,due to reasons such as sensor design and precision,the obtained point cloud usually has missing geometry and sparseness.To solve this problem,this paper proposes a point cloud completion algorithm based on multi-stage fractal combination.In the first stage,the input point cloud is sampled multiple times and features are extracted separately,then the pyramid model is used to generate a point cloud with multi-scale geometry loss,and finally,the generated point cloud is spliced with the input point cloud.In the second stage,KNN clustering and PointNet stacking network are used to extract local features,and the spliced point cloud is down-sampled as a rough prediction,and fi-nally,the rough prediction is combined with the local input folding network to generate a refined high-quality point cloud.This algorithm is based on local to overall multi-stage completion,and the loss function can be adjusted for different stages,which ef-fectively optimizes the completion process and achieves good completion results in the ShapeNet dataset.关键词
点云补全/多阶段/分形组合/几何形状缺失/稀疏性缺失Key words
point cloud completion/multi-stage/fractal combination/missing geometry/missing sparsity分类
信息技术与安全科学引用本文复制引用
曾伟平,陈俊洪,Muhammad ASIM,刘文印,杨振国..基于多阶段分形组合的点云补全算法[J].计算机与现代化,2023,(12):24-29,6.基金项目
国家自然科学基金资助项目(91748107,62076073,61902077) （91748107,62076073,61902077）
广东省引进创新科研团队计划项目(2014ZT05G157) （2014ZT05G157）
广东省基础与应用基础研究基金资助项目(2020A1515010616) （2020A1515010616）
广东省科技创新战略专项资金资助项目(pdjh2020a0173) （pdjh2020a0173）
