{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T04:21:08Z","timestamp":1726806068549},"reference-count":47,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T00:00:00Z","timestamp":1726704000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"U.S. National Institutes of Health","award":["R56 DK113819","R01DK127310"]},{"name":"Bill & Melinda Gates Foundation, Seattle, WA","award":["OPP1171395"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"In dietary assessment using a single-view food image, an object of known size, such as a checkerboard, is often placed manually in the camera\u2019s view as a scale reference to estimate food volume. This traditional scale reference is inconvenient to use because of the manual placement requirement. Consequently, utensils, such as plates and bowls, have been suggested as alternative references. Although these references do not need a manual placement procedure, there is a unique challenge when a dining bowl is used as a reference. Unlike a dining plate, whose shallow shape does not usually block the view of the food, a dining bowl does obscure the food view, and its shape may not be fully observable from the single-view food image. As a result, significant errors may occur in food volume estimation due to the unknown shape of the bowl. To address this challenge, we present a novel method to premeasure both the size and shape of the empty bowl before it is used in a dietary assessment study. In our method, an image is taken with a labeled paper ruler adhered to the interior surface of the bowl, a mathematical model is developed to describe its shape and size, and then an optimization method is used to determine the bowl parameters based on the locations of observed ruler makers from the bowl image. Experimental studies were performed using both simulated and actual bowls to assess the reliability and accuracy of our bowl measurement method.<\/jats:p>","DOI":"10.3390\/s24186058","type":"journal-article","created":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T12:12:27Z","timestamp":1726747947000},"page":"6058","source":"Crossref","is-referenced-by-count":0,"title":["Dining Bowl Modeling and Optimization for Single-Image-Based Dietary Assessment"],"prefix":"10.3390","volume":"24","author":[{"given":"Boyang","family":"Li","sequence":"first","affiliation":[{"name":"Department of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-7948-9205","authenticated-orcid":false,"given":"Mingui","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA"},{"name":"Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15260, USA"},{"name":"Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15260, USA"}]},{"given":"Zhi-Hong","family":"Mao","sequence":"additional","affiliation":[{"name":"Department of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA"},{"name":"Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15260, USA"}]},{"given":"Wenyan","family":"Jia","sequence":"additional","affiliation":[{"name":"Department of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Xu, C., He, Y., Khannan, N., Parra, A., Boushey, C., and Delp, E. 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