A sketch-based semantic retrieval approach for 3D CAD models

Abstract

During the new product development process, reusing the existing CAD models could avoid designing from scratch and decrease human cost. With the advent of big data, how to rapidly and efficiently find out suitable 3D CAD models for design reuse is taken more attention. Currently the sketch-based retrieval approach makes search more convenient, but its accuracy is not high enough; on the other hand, the semantic-based retrieval approach fully utilizes high level semantic information, and makes search much closer to engineers’ intent. However, effectively extracting and representing semantic information from data sets is difficult. Aiming at these problems, we proposed a sketch-based semantic retrieval approach for reusing 3D CAD models. Firstly a fine granularity semantic descriptor is designed for representing 3D CAD models; Secondly, several heuristic rules are adopted to recognize 3D features from 2D sketch, and the correspondences between 3D feature and 2D loops are built; Finally, semantic and shape similarity measurements are combined together to match the input sketch to 3D CAD models. Hence the retrieval accuracy is improved. A sketch-based prototype system is developed. Experimental results validate the feasibility and effectiveness of our proposed approach.