Cuong Pham, D. Jackson, Johannes Schöning, Tom Bartindale, T. Plötz, P. Olivier
{"title":"FoodBoard: surface contact imaging for food recognition","authors":"Cuong Pham, D. Jackson, Johannes Schöning, Tom Bartindale, T. Plötz, P. Olivier","doi":"10.1145/2493432.2493522","DOIUrl":null,"url":null,"abstract":"We describe FoodBoard, an instrumented chopping board that uses optical fibers and embedded camera imaging to identify unpackaged ingredients during food preparation on its surface. By embedding the sensing directly, and robustly, in the surface of a chopping board we also demonstrate how surface contact optical sensing can be used to realize the portability and privacy required of technology used in a setting such as a domestic kitchen. FoodBoard was subjected to a close to real-world evaluation in which 12 users prepared actual meals. FoodBoard compared favourably with existing unpackaged food recognition systems, classifying a larger number of distinct food ingredients (12 incl. meat, fruit, vegetables) with an average accuracy of 82.8%.","PeriodicalId":262104,"journal":{"name":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2493432.2493522","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
We describe FoodBoard, an instrumented chopping board that uses optical fibers and embedded camera imaging to identify unpackaged ingredients during food preparation on its surface. By embedding the sensing directly, and robustly, in the surface of a chopping board we also demonstrate how surface contact optical sensing can be used to realize the portability and privacy required of technology used in a setting such as a domestic kitchen. FoodBoard was subjected to a close to real-world evaluation in which 12 users prepared actual meals. FoodBoard compared favourably with existing unpackaged food recognition systems, classifying a larger number of distinct food ingredients (12 incl. meat, fruit, vegetables) with an average accuracy of 82.8%.