{"title":"基于局部二值模式和运动历史图像的运动描述:在人体运动识别中的应用","authors":"Ping Guo, Z. Miao","doi":"10.1109/HAVE.2008.4685319","DOIUrl":null,"url":null,"abstract":"This paper presents a new human motion recognition method based on motion history image (MHI) and local binary pattern (LBP). MHI describes human motion sequence in one gray level image and LBP extracts its texture features. LBP feature image is built and chi square distance is applied to compute matching cost. Experiments are conducted with encouraging results which show a success of applying LBP in motion recognition.","PeriodicalId":113594,"journal":{"name":"2008 IEEE International Workshop on Haptic Audio visual Environments and Games","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Motion description with local binary pattern and motion history image: Application to human motion recognition\",\"authors\":\"Ping Guo, Z. Miao\",\"doi\":\"10.1109/HAVE.2008.4685319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new human motion recognition method based on motion history image (MHI) and local binary pattern (LBP). MHI describes human motion sequence in one gray level image and LBP extracts its texture features. LBP feature image is built and chi square distance is applied to compute matching cost. Experiments are conducted with encouraging results which show a success of applying LBP in motion recognition.\",\"PeriodicalId\":113594,\"journal\":{\"name\":\"2008 IEEE International Workshop on Haptic Audio visual Environments and Games\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Workshop on Haptic Audio visual Environments and Games\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HAVE.2008.4685319\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Workshop on Haptic Audio visual Environments and Games","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HAVE.2008.4685319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Motion description with local binary pattern and motion history image: Application to human motion recognition
This paper presents a new human motion recognition method based on motion history image (MHI) and local binary pattern (LBP). MHI describes human motion sequence in one gray level image and LBP extracts its texture features. LBP feature image is built and chi square distance is applied to compute matching cost. Experiments are conducted with encouraging results which show a success of applying LBP in motion recognition.