{"title":"Eating Activity Detection from Images Acquired by a Wearable Camera.","authors":"Xin Sun, Hongxun Yao, Wenyan Jia, Mingui Sun","doi":"10.1145/2526667.2526681","DOIUrl":null,"url":null,"abstract":"<p><p>We present an eating activity detection method via automatic detecting dining plates from images acquired chronically by a wearable camera. Convex edge segments and their combinations within each input image are modeled with respect to probabilities of belonging to candidate ellipses. Then, a dining plate is determined according to a confidence score. Finally, the presence/absence of an eating event in an image sequence is determined by analyzing successive frames. Our experimental results verified the effectiveness of this method.</p>","PeriodicalId":92581,"journal":{"name":"SenseCam 2013 : proceedings of the 4th SenseCam Conference : SenseCam and Pervasive Imaging 2013 : San Diego, USA, November 18-19, 2013. SenseCam (Conference) (4th : 2013 : San Diego, Calif.)","volume":"2013 ","pages":"80-81"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2526667.2526681","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SenseCam 2013 : proceedings of the 4th SenseCam Conference : SenseCam and Pervasive Imaging 2013 : San Diego, USA, November 18-19, 2013. SenseCam (Conference) (4th : 2013 : San Diego, Calif.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2526667.2526681","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
We present an eating activity detection method via automatic detecting dining plates from images acquired chronically by a wearable camera. Convex edge segments and their combinations within each input image are modeled with respect to probabilities of belonging to candidate ellipses. Then, a dining plate is determined according to a confidence score. Finally, the presence/absence of an eating event in an image sequence is determined by analyzing successive frames. Our experimental results verified the effectiveness of this method.
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