Joint Feature Mapping for End-to-End Sketch-Based 3D Model Retrieval

Sketch based 3D model retrieval has the characteristics including diversity of intra-class sketches,complexity of the 3D models,and the huge inter-domain differences between the sketches and 3D models.The interaction of these characteristics makes the sketch-based 3D model retrieval task becomes particularly difficult.To solve the problem,an end-to-end sketch-3D model retrieval framework based on joint feature mapping is proposed.Firstly,the 3D model is transformed into a set of 2D views to establish the shared data space of cross-domain data.Then,through network weight sharing,the end-to-end triplet metric learning network is established,and the joint feature mapping of the cross-domain data,sketches and views,is realized.Finally,based on the joint feature distribution,four kinds of similarity evaluation algorithms between sketches and 3D models are proposed to realize sketch based 3D model retrieval.The retrieval precisions in the large public data sets SHREC2013 and SHREC2014 are 81.8%and 75.6%,respectively,and have demonstrated that the algorithm in this paper is better than the state-of-the art methods in seven indexes of PR curve,NN,FT,ST,E,DCG and MAP.