三维文物点云模型配准优化算法  

Registration Optimization Algorithm for 3D Cultural Relics Point Clouds Model

作　　者：孙家泽[1] 陈皓[1] 耿国华[2] 

机构地区：[1]西安邮电大学计算机学院,西安710121 [2]西北大学信息科学与技术学院,西安710127

出　　处：《计算机辅助设计与图形学学报》2016年第7期1068-1074,共7页Journal of Computer-Aided Design & Computer Graphics

基　　金：国家自然科学基金(61203311;611721701);陕西省自然科学基金(2015JM6359);西安市科技计划项目(CXY1516(4));陕西省教育厅自然科学基金(15JK1672;15JK1678);陕西省普通高等学校重点学科专项资金建设项目

摘　　要：针对文物碎片配准过程中碎片点云之间不存在包含关系、对应点难以确定和配准效率低的问题,提出一种基于群体智能的文物点云数据配准优化算法.该算法利用曲率显著特征点的Hausdorff距离来确定初始对应点集,利用离散混沌细菌群体趋药算法求解得到最优的粗配准点对,采用混沌细菌群体趋药算法寻找最优的旋转和平移参数完成精配准.文中算法扩展了配准算法的使用范围,提高了配准的精度和效率,最后以具体的兵马俑碎片实例验证了该算法的有效性.Aiming at the problem of low efficient registration without mutual information and accurate corresponding points of 3D fragments in the process of the registration for the 3D cultural relic's fragments, this paper proposes registration optimization algorithm based on swarm intelligence. The algorithm determines the initial matching points with Hausdorff's distance of curvature feature points. The optimal corresponding points in coarse registration are obtained by discrete chaotic bacterial colony chemo taxis algorithm and the optimal coordinate transform is estimated by chaotic bacterial colony chemo taxis algorithm. The new method improves the precision and efficiency of registration, and expands the scope of application of the registration algorithm. Classical examples of Terra-Cotta Warriors broken fragments show that the method is effective in registration of the 3D cultural relic's fragments.

关 键 词：混沌细菌群体趋药算法 三维模型 配准优化 文物点云 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]