摘要
随着网络上使用或存储在数据库中的三维模型数量迅速增加,如何从大量的三维模型中检索到相似的三维模型变得十分必要。由于目前基于形状的三维模型检索不包含语义概念,因而检索的结果已不能满足用户的需要。针对此现象提出一种新方法,即结合语义和形状特征的三维模型检索。使用K-means算法把形状特征聚类到语义群中,空间关系消除具有相似外观模型之间的歧义。利用普林斯顿形状基准数据库进行实验,结果证明了该方法的可行性。
Along with the number of 3D models used on the web or stored in databases increasing rapidly, it becomes necessary for the us- ers to retrieve a similar 3D model from huge amount of 3D models. Since the shape-based 3D model retrieval does not include semantics concept, so the result of retrieval can no longer meet the needs of the users. For this phenomenon, we propose a new 3D model retrieval method which combines the semantics with the shape features. K-means algorithm is employed to cluster the shape features to the semantic group. Spatial relationships are used to disambiguate among models with similar appearance. The Princeton Shape Benchmark Database is used to in- terpret the experimental resuhs, and it demonstrates the feasibility of the method.
出处
《计算机应用与软件》
CSCD
北大核心
2012年第7期294-297,共4页
Computer Applications and Software
