{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T11:16:27Z","timestamp":1777288587351,"version":"3.51.4"},"reference-count":33,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,7,22]],"date-time":"2021-07-22T00:00:00Z","timestamp":1626912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science Foundation of China","award":["61703306"],"award-info":[{"award-number":["61703306"]}]},{"DOI":"10.13039\/501100006606","name":"Natural Science Foundation of Tianjin","doi-asserted-by":"publisher","award":["18JCYBJC85000"],"award-info":[{"award-number":["18JCYBJC85000"]}],"id":[{"id":"10.13039\/501100006606","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Doctoral Foundation of Tianjin Normal University","award":["52XB1302"],"award-info":[{"award-number":["52XB1302"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Human motion retrieval and analysis is a useful means of activity recognition to 3D human bodies. An efficient method is proposed to estimate human motion by using symmetric joint points and limb features of various limb parts based on regression task. We primarily obtain the 3D coordinates of symmetric joint points based on the located waist and hip points. By introducing three critical feature points on torso and symmetric joint points\u2019 matching on motion video sequences, the 3D coordinates of symmetric joint points and its asymmetric limb features will not be affected by shading and interference of limb on different postures. With the asymmetric limb features of various human parts, a dynamic regulated Fuzzy neural network (DRFNN) is proposed to estimate human motion for different asymmetric postures using learning algorithm of network parameters and weights. Finally, human sequential actions corresponding to different asymmetric postures are presented according to the best retrieval results by DRFNN based on 3D human action database. Experiments show that compared with the traditional adaptive self-organizing fuzzy neural network (SOFNN) model, the proposed algorithm has higher estimation accuracy and better presentation results compared with the existing human motion analysis algorithms.<\/jats:p>","DOI":"10.3390\/sym13081317","type":"journal-article","created":{"date-parts":[[2021,7,22]],"date-time":"2021-07-22T22:37:14Z","timestamp":1626993434000},"page":"1317","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An Efficient Dynamic Regulated Fuzzy Neural Network for Human Motion Retrieval and Analysis"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7103-7212","authenticated-orcid":false,"given":"Xin","family":"Huang","sequence":"first","affiliation":[{"name":"College of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanping","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuqin","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4490","DOI":"10.1109\/TIP.2018.2839522","article-title":"Object-location-aware hashing for multi-label image retrieval via automatic mask learning","volume":"27","author":"Huang","year":"2018","journal-title":"IEEE Trans. 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