计算机科学 ›› 2011, Vol. 38 ›› Issue (11): 248-251.

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三维网格模型增量式聚类检索

孙晓鹏,纪燕杰,李翠芳,魏小鹏   

  1. (辽宁师范大学计算机与信息技术学院 大连116029)(大连大学辽宁省先进设计与智能计算省部共建教育部重点实验室 大连116622)
  • 出版日期:2018-12-01 发布日期:2018-12-01

3D Mesh Model Retrieval Using Incremental Clustering

  • Online:2018-12-01 Published:2018-12-01

摘要: 针对大规模三维网格模型库中的形状检索问题,提出了基于增量式聚类的三维形状描述和检索方法。首先根据三维模型的曲率分布直方图提取特征点得到特征向量;然后根据特征向量描述建立模型库的关键词词典;在特征 匹配阶段基于增量聚类方法判断目标模型的特征向量是否属于某一个关键词,并根据增量聚类的结果更新检索关键词词典;最后匹配特征向量检索模型库中与目标模型形状相同和相近的三维网格模型。相关实验结果证明了该方法快速有效,具有较高的准确性。

关键词: 三维模型检索,增量聚类,特征直方图,特征向量匹配

Abstract: For the model retrieve of largcscale threcdimensional inefficiency, this paper presented a threcdimensional model retrieval method based on the idea of incremental clustering. Firstly, for the models among the model base, constructed a retrieval words codebook. Then extracted the feature points to attain the feature vector of models according to the feature histogram,after that,followed by an incremental clustering method and update retrieval words codebook. Finally,a feature vector matching method was used to determine whether the model base contains the models which is related to the target model. Experimental results show that our implementation can get the retrieval result rapidly and precisely.

Key words: 3D mesh model,Incremental clustering,Featurc histogram,Fcature vector matching

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