摘要
为健壮处理包含尖锐特征或欠采样的数据点集,通过对基于边界推进曲面重建技术的扩展,提出一种分片驱动的、特征敏感的对无方向散乱数据点集进行曲面重建的算法.在一个光滑阈值的控制下,将曲面重建过程分成分片重建和特征缝合2个阶段.在分片重建中,从光滑的种子三角化区域开始进行边界推进三角化,并通过拓扑元素分类与特征检测对边界光顺和特征重定位,以进一步扩展该分片,重复该过程,得到对光滑区域三角化的一系列光滑分片;特征缝合阶段,在边界推进过程中将所有分离的分片或分片中的缝隙缝合在特征区域.这种两阶段的三角化策略可有效地处理含尖锐特征或不规则采样如不充分采样的点集,无需保证拓扑完整性的复杂数学测试,如协变分析和三角形相交检测等,基于局部光滑曲面的求交,可有效地恢复采样点集丢失的特征信息.实验结果表明,采用文中算法能健壮处理不规则采样点集,并生成特征敏感的高质量网格.
In order to deal with point sets with sharp features or non-sufficient sampled points,this paper presents a segment driven feature-sensitive triangulation algorithm as an extension to general advancing front technique,to reconstruct high quality triangle meshes from unorganized,un-oriented point sets.With a smoothness threshold,the triangulation process is divided into two stages as segment reconstruction and stitching reconstruction.The segment reconstruction triangulates smooth regions starting from smooth seed triangulations,and by classifying elements and detecting features,filers out boundary outliers and relocate feature vertices in order to further advance fronts of these smooth segments.The stitching reconstruction stitches the gaps among segments or smooth regions of segments while advancing fronts of all segments,and relocates or inserts new feature vertices by intersections of local smooth surfaces.With this two-stage triangulation technique,the algorithm can robustly treat point sets with sharp features or bad sampling condition such as insufficient sampling,and especially avoids the expensive computation such as covariance analysis and intersection tests used in the general advancing front technique.Experiment results show that feature-sensitive quality triangulations can be achieved.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2010年第9期1529-1537,共9页
Journal of Computer-Aided Design & Computer Graphics
基金
江苏省高新技术产业发展项目(JHB05-31)资助
关键词
曲面重建
边界推进
尖锐特征
surface reconstruction
advancing front
sharp feature
