Classification and Retrieval of Archaeological Potsherds Using Histograms of Spherical Orientations
Classification and Retrieval of Archaeological Potsherds Using Histograms of Spherical Orientations
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DOI：
10.1145/2948069
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发表时间：
2016-11-01
影响因子：
2.4
通讯作者：
Marchand-Maillet, Stephane
中科院分区：
文献类型：
--
作者：
Roman-Rangel, Edgar;Jimenez-Badillo, Diego;Marchand-Maillet, Stephane
我们解决的问题的统计描述的3D表面的自动分类和检索考古陶片的目的。这些都是考古学中特别有趣的问题，因为陶器在考古发掘中有大量的发现。事实上，对陶片的分析为理解古代群体的文化提供了相关线索。特别是，我们开发了一种新的局部形状描述符的3D表面，称为直方图的球形方向（HoSO），我们使用的结合袋的话的方法来计算3D表面之间的视觉相似性。给定3D表面上的感兴趣点，其局部形状描述符（HoSO）捕获其相邻点的球形方向的分布。反过来，这些球面取向是相对于感兴趣的点本身在方位角和天顶轴上计算的。所提出的HoSO是不变的尺度变换和旋转和噪声具有很强的鲁棒性。此外，它是高效的，因为它只利用3D点的位置信息，而忽略其他类型的信息，如面或法线。我们进行了一组3D表面上的实验，代表陶片从特奥蒂瓦坎文明和进一步验证的一组3D模型的通用对象。我们的研究结果表明，我们的方法是有效的描述3D模型，它提高了分类性能相对于以前的本地描述符。
We address the problem of the statistical description of 3D surfaces with the purpose of automatic classification and retrieval of archaeological potsherds. These are particularly interesting problems in archaeology, as pottery comprises a great volume of findings in archaeological excavations. Indeed, the analysis of potsherds brings relevant cues for understanding the culture of ancient groups. In particular, we develop a new local shape descriptor for 3D surfaces, called the histogram of spherical orientations (HoSO), which we use in combination with a bag-of-words approach to compute visual similarity between 3D surfaces. Given a point of interest on a 3D surface, its local shape descriptor (HoSO) captures the distribution of the spherical orientations of its neighboring points. In turn, those spherical orientations are computed with respect to the point of interest itself, both in the azimuth and the zenith axis. The proposed HoSO is invariant to scale transformations and highly robust to rotation and noise. In addition, it is efficient, as it only exploits the information of the position of the 3D points and disregards other types of information like faces or normals. We performed experiments on a set of 3D surfaces representing potsherds from the Teotihuacan civilization and further validations on a set of 3D models of generic objects. Our results show that our methodology is effective for describing 3D models and that it improves classification performance with respect to previous local descriptors.