中国光学（中英文）2024，Vol.17Issue(5)：1125-1138,14.DOI:10.37188/CO.2024-0022
模型自适应的扫描视点自动规划
Model adaptive scanning viewpoint automatic planning
摘要
Abstract
Teaching scans are cumbersome and have poor versatility when performing scan reconstruction.Viewpoint planning has continued to focus on automatically obtaining the minimum set of viewpoints cover-ing the model.To realize automated 3D scanning and reconstruction of parts with different complexity levels,we study issues such as viewpoint redundancy,viewpoint occlusion,and binocular reconstruction constraints that may occur during viewpoint planning.First,given the difficulty of completely scaning the model with existing viewpoint planning,Lloyd's algorithm is improved by analyzing the characteristics of surface struc-tured light scanning and the energy function of Euclidean distance and normal vector deviation is applied to perform Voronoi partitioning of the model to generate an initial scanning viewpoint.Then,to address the viewpoint redundancy problem,an iterative algorithm for splitting the initial scanning viewpoints is pro-posed.Finally,given the problem that the generated viewpoints are prone to occlusion,a line-of-sight de-oc-clusion strategy is proposed.Moreover,to improve the model coverage,a method of using panning view-points is proposed.The experimental results show that under the optimal number of viewpoints,the coverage rate of automobile castings and shells reaches more than 94%,and that of the simple curved automobile sheet metal reaches more than 99.5%,and automatic planning and scanning of the automotive steering knuckle is realized.Planning scanning meets the coverage and efficiency requirements of automatic viewpoint planning and the adaptability requirements for parts with different complexity levels.关键词
视点规划/Voronoi划分/视点冗余/视点遮挡/双目约束Key words
viewpoint planning/Voronoi division/viewpoint redundancy/viewpoint occlusion/binocular constraints分类
信息技术与安全科学引用本文复制引用
杨国庆,王立忠,任茂栋,徐建宁,赵建博,王森,李壮壮..模型自适应的扫描视点自动规划[J].中国光学（中英文）,2024,17(5):1125-1138,14.基金项目
国家重点研发计划项目(No.2022YFB4601802) Supported by the National key R&D Program of China(No.2022YFB4601802) （No.2022YFB4601802）
