On visual similarity based 3D model retrieval
On visual similarity based 3D model retrieval
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DOI：
10.1111/1467-8659.00669
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发表时间：
2003-01-01
影响因子：
2.5
通讯作者：
Ming, OY
中科院分区：
文献类型：
--
作者：
Chen, DY;Tian, XP;Ming, OY
随着越来越多的3D建模和数字化工具被开发用于日益增长的应用，大量的3D模型被创建并在Web上可用。因此，基于内容的三维模型检索技术变得十分必要。提出了一种基于视觉相似度的三维模型检索系统。该方法通过视觉相似性来衡量3D模型之间的相似性，其主要思想是如果两个3D模型相似，则它们在所有视角下也看起来相似。因此，对象的100个不包括对称性的正交投影被Zernike矩和傅立叶描述子作为特征编码以供以后检索。基于视觉相似性的方法对相似变换、噪声、模型退化等具有较强的鲁棒性，并提供了比其他三种竞争方法(精度-召回评估图)高42%、94%和25%的性能(精度-召回评估图)：(1)Funkhoer等人开发的球面调和方法，(2)MPEG-7形状3D描述符，和(3)MPEG-7多视点描述符。拟议的系统在网上供实际试用(http://3d.csie.ntu.edu.tw)，)，数据库包含从万维网网页收集的10,000多个公开提供的三维模型。此外，还提供了一个用户友好的界面来通过绘制2D形状来检索3D模型。在使用Pentium IV 2.4 GHz CPU的服务器上，检索速度足够快，直接通过3D模型查询大约需要2秒，而通过手绘2D形状查询大约需要0.1秒。
A large number of 3D models are created and available on the Web, since more and more 3D modelling and digitizing tools are developed for ever increasing applications. The techniques for content-based 3D model retrieval then become necessary. In this paper, a visual similarity-based 3D model retrieval system is proposed. This approach measures the similarity among 3D models by visual similarity, and the main idea is that if two 3D models are similar they also look similar from all viewing angles. Therefore, one hundred orthogonal projections of an object, excluding symmetry, are encoded both by Zernike moments and Fourier descriptors as features for later retrieval. The visual similarity-based approach is robust against similarity transformation, noise, model de-generacy etc., and provides 42%, 94% and 25% better performance (precision-recall evaluation diagram) than three other competing approaches: (1)the spherical harmonics approach developed by Funkhouser et al., (2)the MPEG-7 Shape 3D descriptors, and (3)the MPEG-7 Multiple View Descriptor. The proposed system is on the Web for practical trial use (http://3d.csie.ntu.edu.tw), and the database contains more than 10,000 publicly available 3D models collected from WWW pages. Furthermore, a user friendly interface is provided to retrieve 3D models by drawing 2D shapes. The retrieval is fast enough on a server with Pentium IV 2.4GHz CPU, and it takes about 2 seconds and 0.1 seconds for querying directly by a 3D model and by hand drawn 2D shapes, respectively.