摘要
提出一种基于深度加权法向映射的三维检索算法 ,从归一化处理后的物体形状出发 ,计算关于视点方向的深度加权表面法向统计分布 ,并将该分布沿视点方向作球面调和分析得到深度加权法向映射特征 。
In this paper, we propose a novel 3D model retrieval algorithm based on a new shape descriptor, “depth weighted normal map”. By means of uniform orthogonal sampling, we represent the shape signature of each model as a statistical distribution of its surface normals weighted by relative depth. The distribution is further processed by spherical harmonics analysis to construct the final shape representation. By calculating the distance between shape descriptors of individual 3D models, a faithful similarity measurement is achieved.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2005年第2期247-252,共6页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60272031)
国家"十五"重大科技攻关项目(2001BA101A0703)
教育部博士点基金(20010335049)
国家重点基础研究发展规划项目(2002CB312100)
浙江省自然科学重点项目(ZD0212)
关键词
三维模型检索
深度加权法向映射
相似变换不变量
均匀正交采样
球面调和分析
D model retrieval
depth weighted normal map
similarity transformation invariance
uniform orthogonal sampling
spherical harmonics analysis
