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dc.contributor.authorAloba, Aishaten_US
dc.contributor.authorFlores, Gianneen_US
dc.contributor.authorWoodward, Juliaen_US
dc.contributor.authorShaw, Alexen_US
dc.contributor.authorCastonguay, Amandaen_US
dc.contributor.authorCuba, Isabellaen_US
dc.contributor.authorDong, Yuzhuen_US
dc.contributor.authorJain, Eaktaen_US
dc.contributor.authorAnthony, Lisaen_US
dc.contributor.editorDiamanti, Olga and Vaxman, Amiren_US
dc.date.accessioned2018-04-14T18:32:44Z
dc.date.available2018-04-14T18:32:44Z
dc.date.issued2018
dc.identifier.issn1017-4656
dc.identifier.urihttp://dx.doi.org/10.2312/egs.20181033
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egs20181033
dc.description.abstractResearch has suggested that children's whole-body motions are different from those of adults. However, research on children's motions, and how these motions differ from those of adults, is limited. One possible reason for this limited research is that there are few motion capture (mocap) datasets for children, with most datasets focusing on adults instead. There are even fewer datasets that have both children's and adults' motions to allow for comparison between them. To address these problems, we present Kinder-Gator, a new dataset of ten children and ten adults performing whole-body motions in front of the Kinect v1.0. The data contains RGB and 3D joint positions for 58 motions, such as wave, walk in place, kick, and point, which have been manually labeled according to the category of the participant (child vs. adult), and the motion being performed. We believe this dataset will be useful in supporting research and applications in animation and whole-body motion recognition and interaction.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectMotion capture
dc.subjectHuman
dc.subjectcentered computing
dc.subjectUser studies
dc.titleKinder-Gator: The UF Kinect Database of Child and Adult Motionen_US
dc.description.seriesinformationEG 2018 - Short Papers
dc.description.sectionheadersAnimation and Simulation
dc.identifier.doi10.2312/egs.20181033
dc.identifier.pages13-16


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