Global and Local Isometry-Invariant Descriptor for 3D Shape Comparison and Partial Matching
文献类型：会议论文
| 作者 | Huai-Yu Wu ; Hongbin Zha; Tao Luo; Xu-Lei Wang; Songde MA
|
| 出版日期 | 2010 |
| 会议日期 | 2010 |
| 会议地点 | San Francisco, California |
| 关键词 | Global And Local Isometry-invariant Descriptor For 3d Shape Comparison And Partial Matching |
| 英文摘要 |
In this paper, based on manifold harmonics, we propose
a novel framework for 3D shape similarity comparison and
partial matching. First, we propose a novel symmetric meanvalue
representation to robustly construct high-quality manifold
harmonic bases on nonuniform-sampling meshes. Then,
based on the manifold harmonic bases constructed, a novel
shape descriptor is presented to capture both of global and local
features of 3D shape. This feature descriptor is isometryinvariant,
i.e., invariant to rigid-body transformations and
non-rigid bending. After characterizing 3D models with the
shape features, we perform 3D retrieval with a up-to-date discriminative
kernel. This kernel is a dimension-free approach
to quantifying the similarity between two unordered featuresets,
thus especially suitable for our high-dimensional feature
data. Experimental results show that our framework can be effectively
used for both comprehensive comparison and partial
matching among non-rigid 3D shapes. |
| 会议录 | IEEE Conference on Computer Vision and Pattern Recognitionn (CVPR 2010)
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12141]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_遥感图像处理团队 |
| 通讯作者 | Huai-Yu Wu |
| 作者单位 | NLPR, CASIA |
| 推荐引用方式 GB/T 7714 | Huai-Yu Wu,Hongbin Zha,Tao Luo,et al. Global and Local Isometry-Invariant Descriptor for 3D Shape Comparison and Partial Matching[C]. 见:. San Francisco, California. 2010. |
入库方式： OAI收割
来源：自动化研究所
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