dc.contributor.author | Kim, Seonghun | en_US |
dc.contributor.author | Balasubramanyam, Adithya | en_US |
dc.contributor.author | Kim, Dubeom | en_US |
dc.contributor.author | Chai, Young Ho | en_US |
dc.contributor.author | Patil, Ashok Kumar | en_US |
dc.contributor.editor | Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta | en_US |
dc.date.accessioned | 2020-05-24T13:52:11Z | |
dc.date.available | 2020-05-24T13:52:11Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-3-03868-106-9 | |
dc.identifier.uri | https://doi.org/10.2312/evs.20201065 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/evs20201065 | |
dc.description.abstract | A motion comparison method using images allows for the motions to be easily recognized and to see differences between each action. However, when using images, orientation differences between similar motions cannot be quantified. Although many studies have been conducted on methods to represent the data and apply detailed motion comparisons, these representations are difficult to understand because the relationship between the motion and the representation is not clear. This paper introduces a novel motion representation method called the Joint-Sphere that enables detailed motion comparisons and an intuitive understanding of each joint movement. In each Joint-Sphere, the movement of a specific joint part is represented. Several Joint- Spheres can be used to represent a full-body motion. The results from a dance motion pattern show that each joint movement can be compared accurately even when several joints are moving quickly. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.rights | Attribution 4.0 International License | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | ] |
dc.subject | Human centered computing | |
dc.subject | Information visualization | |
dc.subject | Human computer interaction (HCI) | |
dc.subject | Visual analytics | |
dc.subject | Visualization toolkits | |
dc.subject | Computing methodologies | |
dc.subject | Motion capture | |
dc.title | Joint-Sphere: Intuitive and Detailed Human Joint Motion Representation | en_US |
dc.description.seriesinformation | EuroVis 2020 - Short Papers | |
dc.description.sectionheaders | Rendering, Images, and Applications | |
dc.identifier.doi | 10.2312/evs.20201065 | |
dc.identifier.pages | 157-161 | |