{"title":"Automated Binocular Vision Measurement of Food Dimensions and Volume for Dietary Evaluation","authors":"Zhi Liu, chao-qun xiang, Tefang Chen","doi":"10.1109/MCSE.2018.243113429","DOIUrl":null,"url":null,"abstract":"We propose a novel binocular vision technique to obtain food dimensions for dietary evaluation. A wearable device acquired images of food samples, which were segmented using the improved Chan-Vese model and compared with virtual objects. Results showed this method to be robust, achieving higher accuracy than conventional correspondence techniques.","PeriodicalId":100659,"journal":{"name":"IMPACT of Computing in Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IMPACT of Computing in Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCSE.2018.243113429","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
We propose a novel binocular vision technique to obtain food dimensions for dietary evaluation. A wearable device acquired images of food samples, which were segmented using the improved Chan-Vese model and compared with virtual objects. Results showed this method to be robust, achieving higher accuracy than conventional correspondence techniques.
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