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A Method of Automatic Semantic Annotation of 3D Model Based on Content Feature

机译:基于内容特征的3D模型自动语义标注方法

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摘要

In response to the existing problem of 3D model semantic retrieval, a method of automatic semantic annotation of 3D model based on content feature is proposed on the basis of Word Net. According to the similarity of content features, this method selects the annotation vocabularies to construct a vocabulary set. Then, some appropriate vocabularies can be selected from the vocabulary set to annotate the 3D models by the similarity between the 3D model to be annotated and the vocabularies in the vocabulary set. In the experiments, three relative parameters are optimized to improve the performance and efficiency. Proved by the experiments, this method proposed in this paper can solve the semantic gap problem. The performance and efficiency of the method is pretty good.
机译:针对3D模型语义检索中存在的问题,提出了一种基于Word Net的基于内容特征的3D模型自动语义标注方法。根据内容特征的相似性,该方法选择注解词汇表来构建词汇表集。然后,可以从词汇表集合中选择一些合适的词汇表,以通过要注释的3D模型和词汇表集合中的词汇表之间的相似性来注释3D模型。在实验中,优化了三个相对参数以提高性能和效率。实验证明,该方法可以解决语义间隙问题。该方法的性能和效率都很好。

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