【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 ,通过比较该特征的距离来度量任意三维模型之间的相似性更多还原

【Abstract】 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.更多还原