Randomized Sub-Volume Partitioning for Part-Based 3D Model Retrieval
Randomized Sub-Volume Partitioning for Part-Based 3D Model Retrieval
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DOI：
10.2312/3dor.20151050
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发表时间：
2015-05
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影响因子：
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通讯作者：
T. Furuya;Seiya Kurabe;Ryutarou Ohbuchi
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文献类型：
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作者：
T. Furuya;Seiya Kurabe;Ryutarou Ohbuchi
给定指定部分形状的查询，基于零件的3D模型检索（P3 DMR）系统将检索其零件匹配查询的3D模型。在计算上，这是相当具有挑战性的;查询必须与具有未知位置、方向和比例的3D模型的部分进行比较。据我们所知，没有算法可以在具有显著大小的数据库上执行P3 DMR（例如，100 K 3D模型），包括多边形汤和其他定义不太明确的形状表示。在本文中，我们提出了一个可扩展的P3 DMR算法，称为基于部分的3D模型检索随机子体积分割，或P3 D-RSVP。为了将部分查询与数据库中的一组（整体）3D模型进行匹配，P3 D-RSVP通过使用具有随机间隔和方向的3D网格来迭代地将3D模型划分为一组子体积。为了快速将查询与数据库中所有模型的所有子卷进行比较，P3 D-RSVP将高维特征散列成紧凑的二进制代码。通过几个基准测试的定量评估表明，P3 D-RSVP能够在2秒内查询50 K模型数据库。
Given a query that specifies partial shape, a Part-based 3D Model Retrieval (P3DMR) system would retrieve 3D models whose part(s) matches the query. Computationally, this is quite challenging; the query must be compared against parts of 3D models having unknown position, orientation, and scale. To our knowledge, no algorithm can perform P3DMR on a database having significant size (e.g., 100K 3D models) that includes polygon soup and other not-so-well-defined shape representations. In this paper, we propose a scalable P3DMR algorithm called Part-based 3D model retrieval by Randomized Sub-Volume Partitioning, or P3D-RSVP. To match a partial query with a set of (whole) 3D models in the database, P3D-RSVP iteratively partitions a 3D model into a set of sub-volumes by using 3D grids having randomized intervals and orientations. To quickly compare the query with all the sub-volumes of all the models in the database, P3D-RSVP hashes high dimensional features into compact binary codes. Quantitative evaluation using several benchmarks shows that the P3D-RSVP is able to query a 50K model database in 2 seconds.