Retrieval and Classification on Textured 3D Models
Retrieval and Classification on Textured 3D Models
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DOI：
10.2312/3dor.20141057
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发表时间：
2014-04
期刊：
影响因子：
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通讯作者：
S. Biasotti;A. Cerri;M. Abdelrahman;Masaki Aono;A. Hamza;M. El-Melegy;A. Farag;V. Garro;
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文献类型：
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作者：
S. Biasotti;A. Cerri;M. Abdelrahman;Masaki Aono;A. Hamza;M. El-Melegy;A. Farag;V. Garro;
本文报告了SHREC‘14 Track：纹理3D模型的检索和分类的结果，其目的是评估当模型因几何形状或纹理或两者而异时检索算法的性能。要搜索的集合由572个纹理网格模型组成，基于几何和纹理进行两级分类。连同数据集一起，提供了96个模型的训练集。赛道上有8名参赛者和22名参赛者，他们要么参加检索比赛，要么参加分类比赛，或者两者兼而有之。评估结果显示了纹理3D检索方法的前景，并揭示了在CIELab而不是RGB颜色空间中处理纹理信息的有趣见解。
This paper reports the results of the SHREC'14 track: Retrieval and classification on textured 3D models, whose goal is to evaluate the performance of retrieval algorithms when models vary either by geometric shape or texture, or both. The collection to search in is made of 572 textured mesh models, having a two-level classification based on geometry and texture. Together with the dataset, a training set of 96 models was provided. The track saw eight participants and the submission of 22 runs, to either the retrieval or the classification contest, or both. The evaluation results show a promising scenario about textured 3D retrieval methods, and reveal interesting insights in dealing with texture information in the CIELab rather than in the RGB colour space.