{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,4,13]],"date-time":"2024-04-13T05:56:05Z","timestamp":1712987765256},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,8,10]],"date-time":"2022-08-10T00:00:00Z","timestamp":1660089600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,8,10]]},"abstract":"<jats:p>With the experiential enhancement of artificial intelligence products, gesture estimation, as a classic computer vision task, has a wide range of application scenarios. Aiming at the current network model that needs to be lightweight in mobile smart products, this paper designs a lightweight gesture pose estimation model based on the CPM (Convolutional Pose Machine) multi-stage human pose estimation network. A comparative experiment based on the RHD open-source data set was conducted to compare and analyze the lightweight CPM gesture estimation model while ensuring accuracy while effectively reducing the amount of model parameters, which provides a basis for the development of real-time mobile terminal gesture pose estimation.<\/jats:p>","DOI":"10.3233\/faia220118","type":"book-chapter","created":{"date-parts":[[2022,8,14]],"date-time":"2022-08-14T23:22:00Z","timestamp":1660519320000},"source":"Crossref","is-referenced-by-count":1,"title":["Lightweight Gesture Pose Estimation Based on CPM Algorithm"],"prefix":"10.3233","author":[{"given":"He","family":"Wang","sequence":"first","affiliation":[{"name":"Heilongjiang University of Science and Technology, College of Electronic and Information Engineering, Harbin 150022, China"}]},{"given":"Qingjiang","family":"Yang","sequence":"additional","affiliation":[{"name":"Heilongjiang University of Science and Technology, College of Electronic and Information Engineering, Harbin 150022, China"}]},{"given":"Qiang","family":"Wang","sequence":"additional","affiliation":[{"name":"Yanshan University, School of Vehicle and Energy, Qinhuangdao 066000, China"}]},{"given":"Liang","family":"Yu","sequence":"additional","affiliation":[{"name":"Heilongjiang University of Science and Technology, College of Electronic and Information Engineering, Harbin 150022, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Modern Management based on Big Data III"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA220118","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,14]],"date-time":"2022-08-14T23:22:01Z","timestamp":1660519321000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA220118"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,10]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia220118","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,10]]}}}