Abstract
To improve the retrieval performance of 3D model,concerning the problem that the semantic-based 3D model retrieval system is hard to support customers' subjective words,a 3D model semantic retrieval method based on content and descriptive text was proposed.This method constructed a semantic tree for 3D models firstly.Then,it calculated the similarity among the input and node of tree by the word statistics method,and got some 3D models from those nodes with high similarity,and a smaller 3D models set by semantic constraint.Finally,user input's 3D model examples may match the shape similarity in the smaller set of 3D model through semantic constraint,and returned search results to users.The WordNet definitions of some words were as input in experiments.The experimental results on PSB show that this method performs better than the content-based 3D model retrieval method on recall-precision.
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