{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:54:35Z","timestamp":1754157275733,"version":"3.41.2"},"reference-count":16,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2009,6,5]],"date-time":"2009-06-05T00:00:00Z","timestamp":1244160000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,6,5]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to present an approach to improve the accuracy of estimating feature points of human body on a vision\u2010based motion capture system (MCS) by using the variable\u2010density self\u2010organizing map (VDSOM).<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>The VDSOM is a kind of self\u2010organizing map (SOM) and has an ability to learn training samples incrementally. The authors let VDSOM learn 3D feature points of human body when the MCS succeeded in estimating them correctly. On the other hand, one or more 3D feature point could not be estimated correctly, the VDSOM is used for the other purpose. The SOM including VDSOM has an ability to recall a part of weight vector which have learned in the learning process. This ability is used to recall correct patterns and complement such incorrect feature points by replacing such incorrect feature points with them.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>Experimental results show that the approach is effective for estimation of human posture robustly compared with the other methods.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The proposed approach is interesting for the collaboration between an MCS and an incremental learning.<\/jats:p><\/jats:sec>","DOI":"10.1108\/17563780910959910","type":"journal-article","created":{"date-parts":[[2009,6,6]],"date-time":"2009-06-06T07:08:48Z","timestamp":1244272128000},"page":"304-326","source":"Crossref","is-referenced-by-count":1,"title":["Robust human posture analysis using incremental learning and recall based on degree of confidence of feature points"],"prefix":"10.1108","volume":"2","author":[{"given":"Atsushi","family":"Shimada","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Madoka","family":"Kanouchi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daisaku","family":"Arita","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rin\u2010Ichiro","family":"Taniguchi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2022021219553644700_b1","unstructured":"Arita, D., Tsuruta, N. and Taniguchi, R. 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