{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:49:54Z","timestamp":1760161794068,"version":"build-2065373602"},"reference-count":61,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,2,2]],"date-time":"2021-02-02T00:00:00Z","timestamp":1612224000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61876170"],"award-info":[{"award-number":["61876170"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Natural Science Fund Youth Science Fund of China","award":["51805168"],"award-info":[{"award-number":["51805168"]}]},{"name":"R&amp;D project of CRRC Zhuzhou Locomotive Co., LTD.","award":["2018GY121"],"award-info":[{"award-number":["2018GY121"]}]},{"name":"Fundamental Research Funds for Central Universities, China University of Geosciences","award":["CUG170692"],"award-info":[{"award-number":["CUG170692"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Hand gesture recognition and hand pose estimation are two closely correlated tasks. In this paper, we propose a deep-learning based approach which jointly learns an intermediate level shared feature for these two tasks, so that the hand gesture recognition task can be benefited from the hand pose estimation task. In the training process, a semi-supervised training scheme is designed to solve the problem of lacking proper annotation. Our approach detects the foreground hand, recognizes the hand gesture, and estimates the corresponding 3D hand pose simultaneously. To evaluate the hand gesture recognition performance of the state-of-the-arts, we propose a challenging hand gesture recognition dataset collected in unconstrained environments. Experimental results show that, the gesture recognition accuracy of ours is significantly boosted by leveraging the knowledge learned from the hand pose estimation task.<\/jats:p>","DOI":"10.3390\/s21031007","type":"journal-article","created":{"date-parts":[[2021,2,2]],"date-time":"2021-02-02T13:01:12Z","timestamp":1612270872000},"page":"1007","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Semi-Supervised Joint Learning for Hand Gesture Recognition from a Single Color Image"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5301-9376","authenticated-orcid":false,"given":"Chi","family":"Xu","sequence":"first","affiliation":[{"name":"School of Automation, China University of Geosciences, Wuhan 430074, China"},{"name":"Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China"},{"name":"Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9615-4498","authenticated-orcid":false,"given":"Yunkai","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Automation, China University of Geosciences, Wuhan 430074, China"},{"name":"Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7416-775X","authenticated-orcid":false,"given":"Jun","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Automation, China University of Geosciences, Wuhan 430074, China"},{"name":"Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7980-9755","authenticated-orcid":false,"given":"Yi","family":"Liu","sequence":"additional","affiliation":[{"name":"CRRC Zhuzhou Electric Locomotive Co., Ltd. 1 TianXin Road, Zhuzhou 412000, China"},{"name":"National Innovation Center of Advanced Rail Transit Equipment, Zhuzhou 412000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1110","DOI":"10.1109\/TMM.2013.2246148","article-title":"Robust part-based hand gesture recognition using kinect sensor","volume":"15","author":"Ren","year":"2013","journal-title":"IEEE Trans. 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