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首页> 外文期刊>Journal of fiber bioengineering and informatics >Virtual Mannequins Retrieval Based on Cluster-based Panoramic Views
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Virtual Mannequins Retrieval Based on Cluster-based Panoramic Views

机译:基于群集全景视图的虚拟人体模特检索

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摘要

With the rapid development of 3D scanners, graphic accelerated hardware and modeling tools, the application of 3D model database is growing in both numbers and sizes, e.g., 3D head and body scan datasets. In this paper, a novel method by using cluster-based panoramic views is proposed for retrieving 3D virtual mannequins. First, a Young Chinese Female Virtual Mannequin (YCFVM) database is established by analyzing various 3D body scan data; second, panoramic views of virtual mannequins are obtained, and the Fourier and Wavelet features of the panoramic views are extracted; third, a multi-scale indexing of the YCFVM dataset is generated for fast matching by using fuzzy clustering for the Wavelet features; finally, the Fourier descriptor is embedded into the feature matching with the generated indexing for obtaining more accurate retrieval results. Experiment results show that the proposed method can achieve better retrieval performance than other descriptors used for virtual mannequin retrieval.
机译:随着3D扫描仪,图形加速硬件和建模工具的快速发展,例如3D头部和身体扫描数据集的数量和大小,3D模型数据库的应用都在增长。本文提出了一种基于聚类的全景图检索3D虚拟人体模型的新方法。首先,通过分析各种3D人体扫描数据,建立了中国青年女性虚拟模特(YCFVM)数据库;其次,获得虚拟人体模型的全景,并提取全景的傅立叶和小波特征。第三,通过对小波特征使用模糊聚类,生成YCFVM数据集的多尺度索引以进行快速匹配。最后,将傅立叶描述符嵌入到与生成的索引匹配的特征中,以获得更准确的检索结果。实验结果表明,与虚拟人体模型检索中使用的其他描述符相比,该方法具有更好的检索性能。

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