基于断裂面匹配的破碎文物的虚拟修复方法
|
摘要
提出一种基于积分不变量的断裂面匹配算法,并利用3D打印技术实现修复结果的仿制。计算在多尺度下断面点的体积积分不变量,寻找邻域相似特征点集形成匹配约束簇。对约束簇进行特征提取及表示,根据簇表面的凹凸互补性,得到初始匹配簇对。运用空间几何一致性约束投票及寻找最大独立集的方法对非正确匹配对进行剪枝,即把粗匹配问题转成最优化问题。在粗匹配的基础上,采用ICPIF进行两两碎块精确对齐。利用三维快速成型设备,将每个文物碎片进行3D打印实现复原结果的仿制,进而验证匹配结果的正确性。实验结果表明,该算法能较好的实现碎块匹配和拼接,实现文物的虚拟修复。
A fracture surface matching algorithm was proposed based on integral invariants and the 3D rapid manufacture technology was performed to create the physical object for virtual model. The points' volume descriptor for multi-scale was computed and similar feature points were found to build matching constraint clusters. Constrained cluster feature was extracted and represented according to convex and concave correspondence of cluster surface. The coarse matching cluster pairs were determined. The method combining spatial geometric consistency constraint's vote and searching the maximum independent set were performed to prune non-matching pairs. Two fragments could be precisely aligned by ICPIF method based on the result of coarse matching. The three dimension rapid manufacture was utilized to generate the physical object for each digital fragment so as to evaluate the accuracy of matching. Experimental results show that the algorithm can achieve better matching and reassemble.
A fracture surface matching algorithm was proposed based on integral invariants and the 3D rapid manufacture technology was performed to create the physical object for virtual model. The points' volume descriptor for multi-scale was computed and similar feature points were found to build matching constraint clusters. Constrained cluster feature was extracted and represented according to convex and concave correspondence of cluster surface. The coarse matching cluster pairs were determined. The method combining spatial geometric consistency constraint's vote and searching the maximum independent set were performed to prune non-matching pairs. Two fragments could be precisely aligned by ICPIF method based on the result of coarse matching. The three dimension rapid manufacture was utilized to generate the physical object for each digital fragment so as to evaluate the accuracy of matching. Experimental results show that the algorithm can achieve better matching and reassemble.
引文
[1]Papaioannou G,Karabassi E A,Theoharis T.Virtual Archaeologist:Assembling the Past[J].IEEE Computer Graphics and Applications(S0272-1716),2001,21(2):53-59.
[2]Winkelbach S,Friedrich M.Pairwise Matching of 3D Fragments Using Cluster Trees[J].International Journal of Computer Vision(S0920-5691),2008,78(1):1-13.
[3]Huang Q X,Flry S,Gelfand N,et al.Reassembling fractured objects by geometric matching[J].ACM Transactions on Graphics(TOG)(S0730-0301),2006,25(3):569-578.
[4]李群辉,周明全,耿国华.基于积分不变量的断裂面匹配算法[J].计算机工程,2012,38(3):156-158.
[5]刘军,周明全,耿国华,等.基于轮廓与断面匹配的秦俑碎片拼接方法[J].计算机工程,2014,40(1):181-185.
[6]Yang Y L,Lai Y K,Hu S M,et al.Robust principal curvatures on multiple scales[C]//Polthier,K.,Sheffer,A.(Eds.),Symp.Geometry Processing.Eurographics,Switzerland:Eurographics Association,2006:223-226.
[7]Merigot Q,Ovsjanikov M,Guibas L J.Voronoi-based Curvature and Feature Estimation from Point Clouds[J].IEEE Transactions on Visualization and Computer Graphics(S1077-2626),2011,17(6):743-756.
[8]Y Shan,B Matei,H S Sawhney,R Kumar,Daniel Huber,and Martial Hebert.Linear Model Hashing and Batch RANSAC for Rapid and Accurate Object Recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition(CVPR 2004),June,2004.USA:IEEE,2004.
[9]Sharp G C,Lee S W,Wehe D K.ICP registration using invariant features[J].IEEE Transactions on Pattern Analysis and Machine Intelligence(S0162-8828),2002,24(1):90-102.
[10]Carr J C,Beatson R K,Cherrie J B,et al.Reconstruction and representation of 3D objects with radial basis functions[C]//Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques.ACM New York,NY,USA,2001:67-76.
[2]Winkelbach S,Friedrich M.Pairwise Matching of 3D Fragments Using Cluster Trees[J].International Journal of Computer Vision(S0920-5691),2008,78(1):1-13.
[3]Huang Q X,Flry S,Gelfand N,et al.Reassembling fractured objects by geometric matching[J].ACM Transactions on Graphics(TOG)(S0730-0301),2006,25(3):569-578.
[4]李群辉,周明全,耿国华.基于积分不变量的断裂面匹配算法[J].计算机工程,2012,38(3):156-158.
[5]刘军,周明全,耿国华,等.基于轮廓与断面匹配的秦俑碎片拼接方法[J].计算机工程,2014,40(1):181-185.
[6]Yang Y L,Lai Y K,Hu S M,et al.Robust principal curvatures on multiple scales[C]//Polthier,K.,Sheffer,A.(Eds.),Symp.Geometry Processing.Eurographics,Switzerland:Eurographics Association,2006:223-226.
[7]Merigot Q,Ovsjanikov M,Guibas L J.Voronoi-based Curvature and Feature Estimation from Point Clouds[J].IEEE Transactions on Visualization and Computer Graphics(S1077-2626),2011,17(6):743-756.
[8]Y Shan,B Matei,H S Sawhney,R Kumar,Daniel Huber,and Martial Hebert.Linear Model Hashing and Batch RANSAC for Rapid and Accurate Object Recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition(CVPR 2004),June,2004.USA:IEEE,2004.
[9]Sharp G C,Lee S W,Wehe D K.ICP registration using invariant features[J].IEEE Transactions on Pattern Analysis and Machine Intelligence(S0162-8828),2002,24(1):90-102.
[10]Carr J C,Beatson R K,Cherrie J B,et al.Reconstruction and representation of 3D objects with radial basis functions[C]//Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques.ACM New York,NY,USA,2001:67-76.