A Texture Similarity Evaluation Method for 3D Models

自20世纪90年代末以来，人们对三维模型的相似性检索进行了各种各样的研究。虽然大多数检索技术关注的是3D模型的形状相似度，但我们的技术允许用户基于纹理模式相似度检索和分类3D模型。为了验证纹理相似度检索技术，利用三维多边形模型和二维纹理图像合成了一组纹理三维模型数据库。通过软件程序对数据库进行分析，并从每个三维模型中提取纹理特征。提取的纹理特征基于HLAC（高阶局部自相关）和分形维数进行计算。通常，这两种纹理特征都被用于分析二维纹理图像。然而，我们将该技术扩展到处理三维体积数据，以从纹理三维模型中提取特征。我们的基于web的实验检索系统以相当可接受的召回准确率成功地检索了纹理三维模型。这种基于纹理图案的检索技术可以与传统的形状相似检索技术结合使用，提高了相似检索的性能。

Various kinds of research have been conducted on similarity retrievals of 3D models since the late 1990's. Although most of the retrieval techniques focus on shape similarity of the 3D models, our technique allows users to retrieve and classify 3D models based on texture pattern similarity. To test our texture similarity retrieval technique, a set of a textured 3D model database was synthesized from 3D polygonal models and 2D texture images. The database was analyzed by software programs, and texture features were extracted from each 3D model. The extracted texture features were computed based on HLAC (higher order local autocorrelation) and fractal dimensions. Often, both kinds of texture features were used for analyzing 2D texture images. However, we extended the techniques to handle three dimensional volumetric data for extracting features from textured 3D models. Our experimental web-based retrieval system successfully retrieved textured 3D models with fairly acceptable recall-precision rates. This retrieval technique which is based on texture patterns can be used in conjunction with traditional shape similarity retrieval techniques, and the technique can enhance similarity retrieval performances.