A similarity retrieval technique for textured 3D models
A similarity retrieval technique for textured 3D models
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DOI：
10.1109/infrkm.2010.5466933
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发表时间：
2010-03
期刊：
影响因子：
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通讯作者：
Motofumi T. Suzuki;Y. Yaginuma;Haruo Kodama
中科院分区：
文献类型：
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作者：
Motofumi T. Suzuki;Y. Yaginuma;Haruo Kodama
本文描述了一种纹理三维模型的相似性检索技术。自20世纪90年代末S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都集中在三维模型的形状相似性上，但我们的技术允许用户根据纹理模式的相似性来检索和分类三维模型。为了测试我们的纹理相似性检索技术，从3D多边形模型和2D纹理图像中合成了一组纹理3D模型数据库。通过软件程序对数据库进行分析，并从每个3D模型中提取纹理特征。基于高阶局部自相关(HLAC)和分形维计算提取的纹理特征。通常，这两种纹理特征都被用于分析2D纹理图像。然而，我们扩展了处理三维体数据的技术，以从纹理3D模型中提取特征。我们的基于Web的实验检索系统成功地检索了纹理3D模型，具有相当好的召回率。这种基于纹理模式的检索技术可以与传统的形状相似检索技术相结合，提高相似检索的性能。
This paper describes a similarity retrieval technique for textured 3D models. 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.