基于VGG-CapsNet的零件手绘草图识别模型

Freehand-Sketched Part Recognition Using VGG-CapsNet

针对概念设计阶段现有CAD系统难以通过手绘草图准确匹配对应的零件的问题,提出预训练网络(VGG)与胶囊网络(CapsNet)相结合的零件手绘草图识别模型(VGG-CapsNet).招募了5名设计师绘制零件草图,构建包含标准件和非标件在内的23类零件手绘草图数据集;设计了组间实验与组内实验,分别构建基于VGG-CapsNet的零件手绘草图识别模型,并与rVGG-13模型、rCNN-13模型的识别结果进行比较.实验结果表明,VGG-CapsNet模型在组间和组内实验中的平均准确率均高于其他2种模型,为零件设计知识的检索与重用提供技术支持.

To solve the problem that the existing CAD system is difficult to match the corresponding parts accurately through the freehand sketch in the conceptual design,a recognition model(VGG-CapsNet)for freehand sketch of part is proposed,which combining the pre-trained network(VGG)and capsule network(CapsNet).Five designers are recruited to sketch parts,and build 23 kinds of freehand sketch of parts in-cluding standard parts and non-standard parts.The between-group experiment and within-group experiment are designed,and then the recognition models of VGG-CapsNet are constructed respectively.The recogni-tion results of the VGG-CapsNet models are compared with the rVGG-13 models and the rCNN-13 models.The experimental results show that the mean accuracy of VGG-CapsNet model is higher than the other two models,which provides technical support for the retrieval and reuse of part design knowledge.