A spectral approach to shape-based retrieval of articulated 3D models
A spectral approach to shape-based retrieval of articulated 3D models
复制标题
DOI：
10.1016/j.cad.2007.02.009
复制
发表时间：
2007-05-01
影响因子：
4.3
通讯作者：
Zhang, Hao
中科院分区：
文献类型：
--
作者：
Jain, Varun;Zhang, Hao
我们提出了一种方法，强大的形状检索数据库中含有铰接的3D模型。每个形状由适当定义的亲和矩阵的特征向量表示，形成谱嵌入，其实现针对刚体变换的归一化、均匀缩放和形状接合（即，弯曲）。使用全局形状描述符在谱域中执行检索。在麦吉尔数据库的三维形状，光谱的方法导致一个绝对的改善检索性能的球谐函数和光场形状描述符。最好的检索结果是使用一个简单的和新颖的基于特征值的描述，我们提出。(c)2007爱思唯尔有限公司版权所有。
We present an approach for robust shape retrieval from databases containing articulated 3D models. Each shape is represented by the eigenvectors of an appropriately defined affinity matrix, forming a spectral embedding which achieves normalization against rigid-body transformations, uniform scaling, and shape articulation (i.e., bending). Retrieval is performed in the spectral domain using global shape descriptors. On the McGill database of articulated 3D shapes, the spectral approach leads to an absolute improvement in retrieval performance for both the spherical harmonic and the light field shape descriptors. The best retrieval results are obtained using a simple and novel eigenvalue-based descriptor we propose. (c) 2007 Elsevier Ltd. All rights reserved.