{"title":"基于轻量级神经网络的手势识别应用研究","authors":"Xinghan Huang, Xiaofu Du, Hedan Liu","doi":"10.1117/12.2653442","DOIUrl":null,"url":null,"abstract":"With the promotion of smart city and other technologies, the application of embedded vision detection equipment is becoming more and more popular, among which gesture recognition is an important application of embedded vision detection equipment. At present, gesture recognition technology on embedded visual detection equipment is mostly implemented by calling API in domestic and foreign researches and products. But this method needs the support of stable communication network and has certain delay problem. To solve the above problems, this paper proposes a lightweight neural network model that can be deployed on embedded devices, which can realize local gesture recognition on embedded terminals without network remote transmission. The network builds a training framework on PyTorch and uses a homemade dataset for training, then lightens the network and finally deploys on raspberry PI for gesture recognition. Experimental results show that this network can run at a higher rate in raspberry PI 4B (4GB), and the model size is greatly reduced. The final recognition effect is good, and it has high practical value.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application research of gesture recognition based on lightweight neural network\",\"authors\":\"Xinghan Huang, Xiaofu Du, Hedan Liu\",\"doi\":\"10.1117/12.2653442\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the promotion of smart city and other technologies, the application of embedded vision detection equipment is becoming more and more popular, among which gesture recognition is an important application of embedded vision detection equipment. At present, gesture recognition technology on embedded visual detection equipment is mostly implemented by calling API in domestic and foreign researches and products. But this method needs the support of stable communication network and has certain delay problem. To solve the above problems, this paper proposes a lightweight neural network model that can be deployed on embedded devices, which can realize local gesture recognition on embedded terminals without network remote transmission. The network builds a training framework on PyTorch and uses a homemade dataset for training, then lightens the network and finally deploys on raspberry PI for gesture recognition. Experimental results show that this network can run at a higher rate in raspberry PI 4B (4GB), and the model size is greatly reduced. The final recognition effect is good, and it has high practical value.\",\"PeriodicalId\":32903,\"journal\":{\"name\":\"JITeCS Journal of Information Technology and Computer Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JITeCS Journal of Information Technology and Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2653442\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JITeCS Journal of Information Technology and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2653442","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application research of gesture recognition based on lightweight neural network
With the promotion of smart city and other technologies, the application of embedded vision detection equipment is becoming more and more popular, among which gesture recognition is an important application of embedded vision detection equipment. At present, gesture recognition technology on embedded visual detection equipment is mostly implemented by calling API in domestic and foreign researches and products. But this method needs the support of stable communication network and has certain delay problem. To solve the above problems, this paper proposes a lightweight neural network model that can be deployed on embedded devices, which can realize local gesture recognition on embedded terminals without network remote transmission. The network builds a training framework on PyTorch and uses a homemade dataset for training, then lightens the network and finally deploys on raspberry PI for gesture recognition. Experimental results show that this network can run at a higher rate in raspberry PI 4B (4GB), and the model size is greatly reduced. The final recognition effect is good, and it has high practical value.