Research on filtering and measurement algorithms based on human point cloud data

International Journal of Intelligent SystemsVolume 37, Issue 12 p. 12252-12266 RESEARCH ARTICLE Research on filtering and measurement algorithms based on human point cloud data Yuxiao Du, Yuxiao Du orcid.org/0000-0003-0450-4559 School of Automation, Guangdong University of Technology, Guangzhou, ChinaSearch for more papers by this authorYuxing Li, Yuxing Li orcid.org/0000-0001-7578-045X School of Automation, Guangdong University of Technology, Guangzhou, ChinaSearch for more papers by this authorZhuocheng Wu, Zhuocheng Wu orcid.org/0000-0003-0053-2341 School of Automation, Guangdong University of Technology, Guangzhou, ChinaSearch for more papers by this authorFeng Chen, Corresponding Author Feng Chen [email protected] orcid.org/0000-0002-4557-8792 School of Automation, Guangdong University of Technology, Guangzhou, China Correspondence Feng Chen, School of Automation, Guangdong University of Technology, 511400 Guangzhou, China. Email: [email protected]Search for more papers by this authorZhiheng Chen, Zhiheng Chen orcid.org/0000-0002-4322-0324 School of Automation, Guangdong University of Technology, Guangzhou, ChinaSearch for more papers by this authorYinglin Li, Yinglin Li orcid.org/0000-0003-4532-735X School of Automation, Guangdong University of Technology, Guangzhou, ChinaSearch for more papers by this author Yuxiao Du, Yuxiao Du orcid.org/0000-0003-0450-4559 School of Automation, Guangdong University of Technology, Guangzhou, ChinaSearch for more papers by this authorYuxing Li, Yuxing Li orcid.org/0000-0001-7578-045X School of Automation, Guangdong University of Technology, Guangzhou, ChinaSearch for more papers by this authorZhuocheng Wu, Zhuocheng Wu orcid.org/0000-0003-0053-2341 School of Automation, Guangdong University of Technology, Guangzhou, ChinaSearch for more papers by this authorFeng Chen, Corresponding Author Feng Chen [email protected] orcid.org/0000-0002-4557-8792 School of Automation, Guangdong University of Technology, Guangzhou, China Correspondence Feng Chen, School of Automation, Guangdong University of Technology, 511400 Guangzhou, China. Email: [email protected]Search for more papers by this authorZhiheng Chen, Zhiheng Chen orcid.org/0000-0002-4322-0324 School of Automation, Guangdong University of Technology, Guangzhou, ChinaSearch for more papers by this authorYinglin Li, Yinglin Li orcid.org/0000-0003-4532-735X School of Automation, Guangdong University of Technology, Guangzhou, ChinaSearch for more papers by this author First published: 21 September 2022 https://doi.org/10.1002/int.23085Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract To obtain the data of noncontact measurement of the human body, the depth camera is used to collect the human body, and the obtained initial data are transformed into the required point cloud data for processing through coordinate transformation, and then the collected three-dimensional point cloud data are preprocessed. The preprocessing includes point cloud downsampling, point cloud filtering, plane segmentation, outlier removal, point cloud surface estimation, and so forth. A new solution for point cloud filtering is proposed, which combines sliding least squares and unification and radius filtering. Compared with the traditional filtering, the effect is smoother, and finally the complete outline of the human body is obtained, and then the human body is measured. The results show that the human body data measured by this scheme is within the range of the relevant standard measurement accuracy. Open Research DATA AVAILABILITY STATEMENT No. Research data are not shared. Volume37, Issue12December 2022Pages 12252-12266 RelatedInformation