论文标题
基于本地形状查询的3D对象检索的索引方案和描述符
An Indexing Scheme and Descriptor for 3D Object Retrieval Based on Local Shape Querying
论文作者
论文摘要
提出了一种基于称为局部形状查询的锤子树的锤距离距离的二进制描述索索引方案。还引入了一个新的二进制抗糊状描述符，名为Quick交点计数更改图像（QUICCI）。这个本地形状的描述符非常小，可以比较。此外，提出了一种适用于Quicci图像的称为加权锤的新型距离函数，提议用于检索应用。索引方案和QUICCI的有效性是在从SHREC2017数据集中得出的8.28亿个Quicci图像上证明的，而使用杂物盒实验显示了Quicci的杂波电阻。
A binary descriptor indexing scheme based on Hamming distance called the Hamming tree for local shape queries is presented. A new binary clutter resistant descriptor named Quick Intersection Count Change Image (QUICCI) is also introduced. This local shape descriptor is extremely small and fast to compare. Additionally, a novel distance function called Weighted Hamming applicable to QUICCI images is proposed for retrieval applications. The effectiveness of the indexing scheme and QUICCI is demonstrated on 828 million QUICCI images derived from the SHREC2017 dataset, while the clutter resistance of QUICCI is shown using the clutterbox experiment.
