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Shape-based retrieval and analysis of 3D models using fuzzy weighted symmetrical depth images

机译:使用模糊加权对称深度图像的基于形状的3D模型检索和分析

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摘要

With the rapid development of 3D scanners, graphic accelerated hardware and 3D modeling tools, the application of 3D model databases is growing in both numbers and sizes, e.g. 3D body scans, head model and virtual mannequins. There is a pressing need for effective content-based 3D model retrieval methods. In this paper, a novel 3D model retrieval approach is proposed by using the Fuzzy Weighted Symmetrical Depth Images (FW-SDI). Firstly, three symmetrical planes of the 3D model are obtained based upon principal plane analysis and sequential quadratic programming, which are the distinctive characteristics of 3D model and perpendicular to each other. Secondly, three novel depth Images (NDI) and three depth differential images (DDI)-are extracted by projecting the 3D surface to the proposed symmetrical planes. The Fourier descriptors of the novel depth Images and depth differential images are calculated. Finally, a fuzzy weighted procedure is conducted for combining the Fourier descriptors of NDI and DDL Experiment results show that the proposed method can achieve better retrieval performance than others.
机译:随着3D扫描仪,图形加速硬件和3D建模工具的飞速发展,3D模型数据库的应用数量和规模都在不断增长,例如, 3D人体扫描,头部模型和虚拟人体模型。迫切需要有效的基于内容的3D模型检索方法。本文利用模糊加权对称深度图像(FW-SDI)提出了一种新颖的3D模型检索方法。首先,基于主平面分析和顺序二次规划,获得了3D模型的三个对称平面,这是3D模型的独特特征,并且彼此垂直。其次,通过将3D表面投影到建议的对称平面上,提取了三个新颖的深度图像(NDI)和三个深度差分图像(DDI)。计算新颖深度图像和深度差分图像的傅立叶描述符。最后,采用模糊加权的方法将NDI和DDL的傅里叶描述子相结合。实验结果表明,该方法具有比其他方法更好的检索性能。

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