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作 者:毛涵杨 彭晨[1] 李晨[1] 王长波[1] MAO Hanyang;PENG Chen;LI Chen;WANG Changbo(School of Computer Science and Technology,East China Normal University,Shanghai 200062,China)
机构地区:[1]华东师范大学计算机科学与技术学院,上海200062
出 处:《浙江大学学报(理学版)》2023年第6期692-700,710,共10页Journal of Zhejiang University(Science Edition)
基 金:国家自然科学基金资助项目(62072183,62002121);上海市2022年度“科技创新行动计划”人工智能科技支撑专项(22511104600).
摘 要:移动立方体(marching cubes,MC)是一种经典的等值面提取算法,但此算法建立在将空间点划分为内部点和外部点基础上,只适用于封闭表面的重建。为解决此问题,提出一种面向开放表面的神经移动立方体算法。通过引入称作无关点的新的空间点分类,因无关点与内部点、外部点以及无关点之间形成的空间区域不存在零等值面,从而可连通三维形状的内部和外部。无关点可通过与表面间的距离直接判断,无需复杂的网络或计算。同时,用引入注意力机制的残差模块代替原网络,以改善重建效果。此外,设计新的曲面细分,借助无关点实现对开放表面的重建。最后,通过加入对边缘的平滑处理,提高边缘部分的重建质量。在多项评估指标下对封闭表面和开放表面进行了测试,证明所提方法不仅能重建封闭表面,而且实现了对开放表面的高质量重建。Marching cubes(MC)is a classic algorithm for isosurface extraction.However,it can only be used to reconstruct closed surfaces,as it requires dividing the space into inside and outside.To solve this problem,a neural marching cubes algorithm for open surfaces is proposed.The key to our method is to introduce a new sort of point position called irrelative point.Since no isosurface exists between irrelevant points and inside or outside points,thus connecting the inside and outside of the target shapes.The determination of irrelevant points does not require complex networks or calculations,and can be directly determined by the distance from points to the surface.Meanwhile,a residual module introducing attention mechanism is adopted to replace the original network.In addition,new tessellations are designed,and open surfaces can be reconstructed with the help of irrelative points.Finally,a smoothing process is incorporated to improve the reconstruction quality of the border.By testing on both closed and open surfaces under various metrics,our experiments show that the proposed method achieves high-quality reconstruction of open surfaces while maintaining the capability of reconstructing closed surfaces.
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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