融合细节与整体特征的三维模型检索方法

A New 3D Model Retrieval Method Combining Local and Global Features

三维模型检索技术能有效提高三维模型的复用率和共享率.为了提高三维模型检索结果的准确率,提出一种融合细节与整体特征的三维模型检索方法,通过SIFT特征和傅立叶描述子特征来对三维模型进行特征描述.分别利用这2种特征来对三维模型进行相似度度量,再通过加权求和的方式对这2种特征进行融合.通过融合这2种特征可以达到同时兼顾三维模型的整体形状特征和局部细节特征,实验证明该方法能提高三维模型检索结果的准确率.

With the rapid increase of 3D models,the 3D model retrieval methods have attracted significant attention.To improve the accuracy of the retrieval result,we propose a new 3Dmodel retrieval method in this paper.Our approach selects the SIFT feature and the Fourier descriptor feature to represent a 3D model.Then we utilize the two different features to calculate the similarity between the query model and the models in the database respectively.Finally,the features are integrated via the linear combination of the distance values they produced using adaptive weights.Experiment results show that our method can improve the accuracy of the retrieval result.