Zhongliang Yang, Ruihong Huang, Yumiao Chen, Song Zhang, Xinhua Mao
{"title":"基于VGG CapsNet的手绘零件识别","authors":"Zhongliang Yang, Ruihong Huang, Yumiao Chen, Song Zhang, Xinhua Mao","doi":"10.3724/sp.j.1089.2021.18774","DOIUrl":null,"url":null,"abstract":": 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 recognition 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.","PeriodicalId":52442,"journal":{"name":"计算机辅助设计与图形学学报","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Freehand-Sketched Part Recognition Using VGG-CapsNet\",\"authors\":\"Zhongliang Yang, Ruihong Huang, Yumiao Chen, Song Zhang, Xinhua Mao\",\"doi\":\"10.3724/sp.j.1089.2021.18774\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": 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 recognition 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.\",\"PeriodicalId\":52442,\"journal\":{\"name\":\"计算机辅助设计与图形学学报\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"计算机辅助设计与图形学学报\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.3724/sp.j.1089.2021.18774\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"计算机辅助设计与图形学学报","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.3724/sp.j.1089.2021.18774","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
Freehand-Sketched Part Recognition Using VGG-CapsNet
: 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 recognition 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.