P. Pouladzadeh, G. Villalobos, R. Almaghrabi, S. Shirmohammadi
{"title":"一种基于支持向量机的食物识别方法在卡路里测量中的应用","authors":"P. Pouladzadeh, G. Villalobos, R. Almaghrabi, S. Shirmohammadi","doi":"10.1109/ICMEW.2012.92","DOIUrl":null,"url":null,"abstract":"Emerging food classification methods play an important role in nowadays food recognition applications. For this purpose, a new recognition algorithm for food is presented, considering its shape, color, size, and texture characteristics. Using various combinations of these features, a better classification will be achieved. Based on our simulation results, the proposed algorithm recognizes food categories with an approval recognition rate of 92.6%, in average.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"48","resultStr":"{\"title\":\"A Novel SVM Based Food Recognition Method for Calorie Measurement Applications\",\"authors\":\"P. Pouladzadeh, G. Villalobos, R. Almaghrabi, S. Shirmohammadi\",\"doi\":\"10.1109/ICMEW.2012.92\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Emerging food classification methods play an important role in nowadays food recognition applications. For this purpose, a new recognition algorithm for food is presented, considering its shape, color, size, and texture characteristics. Using various combinations of these features, a better classification will be achieved. Based on our simulation results, the proposed algorithm recognizes food categories with an approval recognition rate of 92.6%, in average.\",\"PeriodicalId\":385797,\"journal\":{\"name\":\"2012 IEEE International Conference on Multimedia and Expo Workshops\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"48\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Multimedia and Expo Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMEW.2012.92\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Multimedia and Expo Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMEW.2012.92","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel SVM Based Food Recognition Method for Calorie Measurement Applications
Emerging food classification methods play an important role in nowadays food recognition applications. For this purpose, a new recognition algorithm for food is presented, considering its shape, color, size, and texture characteristics. Using various combinations of these features, a better classification will be achieved. Based on our simulation results, the proposed algorithm recognizes food categories with an approval recognition rate of 92.6%, in average.