CM-BOF: visual similarity-based 3D shape retrieval using Clock Matching and Bag-of-Features
CM-BOF: visual similarity-based 3D shape retrieval using Clock Matching and Bag-of-Features
复制标题
CM-BOF：使用时钟匹配和特征袋进行基于视觉相似性的 3D 形状检索
DOI：
10.1007/s00138-013-0501-5
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发表时间：
2013-11-01
影响因子：
3.3
通讯作者：
Xiao, Jianguo
中科院分区：
文献类型：
--
作者：
Lian, Zhouhui;Godil, Afzal;Xiao, Jianguo
基于内容的三维物体检索已成为许多研究领域的一个活跃课题。本文提出了一种新的基于视觉相似性的三维形状检索方法（CM-BOF）。具体来说，姿态归一化首先应用于每个对象以生成其规范姿态，然后归一化的对象由在给定测地线球体的顶点上捕获的一组深度缓冲图像表示。然后，每幅图像被描述为一个词直方图获得的图像的显着的局部特征的矢量量化。最后，一种有效的多视图形状匹配方案（即，时钟匹配）被用来衡量两个模型之间的差异。当应用CM-BOF方法在非刚性3D形状检索中时，多维缩放（MDS）应在姿态归一化之前使用以计算每个对象的标准形。本文还研究了CM-BOF方法的几个关键问题，包括视图数、码书、训练数据和距离函数的影响。实验结果表明：（1）与传统的Bag-of-Features方法相比，CM-BOF方法无需耗时的聚类过程，无需构造码本;（2）在刚性和非刚性三维形状检索应用中，该方法上级或优于现有技术.
Content-based 3D object retrieval has become an active topic in many research communities. In this paper, we propose a novel visual similarity-based 3D shape retrieval method (CM-BOF) using Clock Matching and Bag-of-Features. Specifically, pose normalization is first applied to each object to generate its canonical pose, and then the normalized object is represented by a set of depth-buffer images captured on the vertices of a given geodesic sphere. Afterwards, each image is described as a word histogram obtained by the vector quantization of the image's salient local features. Finally, an efficient multi-view shape matching scheme (i.e., Clock Matching) is employed to measure the dissimilarity between two models. When applying the CM-BOF method in non-rigid 3D shape retrieval, multidimensional scaling (MDS) should be utilized before pose normalization to calculate the canonical form for each object. This paper also investigates several critical issues for the CM-BOF method, including the influence of the number of views, codebook, training data, and distance function. Experimental results on five commonly used benchmarks demonstrate that: (1) In contrast to the traditional Bag-of-Features, the time-consuming clustering is not necessary for the codebook construction of the CM-BOF approach; (2) Our methods are superior or comparable to the state of the art in applications of both rigid and non-rigid 3D shape retrieval.