{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T02:29:25Z","timestamp":1780972165449,"version":"3.54.1"},"reference-count":27,"publisher":"ASME International","issue":"3","license":[{"start":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T00:00:00Z","timestamp":1696809600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.asme.org\/publications-submissions\/publishing-information\/legal-policies"}],"funder":[{"DOI":"10.13039\/501100001868","name":"National Science Council","doi-asserted-by":"publisher","award":["109-2221-E-007-064-MY3"],"award-info":[{"award-number":["109-2221-E-007-064-MY3"]}],"id":[{"id":"10.13039\/501100001868","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["asmedigitalcollection.asme.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Customization is an increasing trend in fashion product industry to reflect individual lifestyles. Previous studies have examined the idea of virtual footwear try-on in augmented reality (AR) using a depth camera. However, the depth camera restricts the deployment of this technology in practice. This research proposes to estimate the six degrees-of-freedom pose of a human foot from a color image using deep learning models to solve the problem. We construct a training dataset consisting of synthetic and real foot images that are automatically annotated. Three convolutional neural network models (deep object pose estimation (DOPE), DOPE2, and You Only Look Once (YOLO)-6D) are trained with the dataset to predict the foot pose in real-time. The model performances are evaluated using metrics for accuracy, computational efficiency, and training time. A prototyping system implementing the best model demonstrates the feasibility of virtual footwear try-on using a red\u2013green\u2013blue camera. Test results also indicate the necessity of real training data to bridge the reality gap in estimating the human foot pose.<\/jats:p>","DOI":"10.1115\/1.4062596","type":"journal-article","created":{"date-parts":[[2023,5,23]],"date-time":"2023-05-23T08:04:37Z","timestamp":1684829077000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":6,"title":["Virtual Footwear Try-On in Augmented Reality Using Deep Learning Models"],"prefix":"10.1115","volume":"24","author":[{"given":"Ting","family":"Chou","sequence":"first","affiliation":[{"name":"National Tsing Hua University Department of Industrial Engineering and Engineering Management, , 101 Kuang Fu Rd, Sec 2, Hsinchu 300 , Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chih-Hsing","family":"Chu","sequence":"additional","affiliation":[{"name":"National Tsing Hua University Department of Industrial Engineering and Engineering Management, , 101 Kuang Fu Rd, Sec 2, Hsinchu 300 , Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengjun","family":"Liu","sequence":"additional","affiliation":[{"name":"Central South University School of Mathematics and Statistics, , No. 932 South Lushan Road Changsha, Hunan 410083 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"33","published-online":{"date-parts":[[2023,10,9]]},"reference":[{"issue":"2","key":"2023100915370281700_CIT0001","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3491226","article-title":"Transform, Warp, and Dress: A New Transformation-Guided Model for Virtual Try-On","volume":"18","author":"Fincato","year":"2022","journal-title":"ACM Trans. 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