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dc.contributor.authorLi, Kunen_US
dc.contributor.authorJiao, Nianhongen_US
dc.contributor.authorLiu, Yebinen_US
dc.contributor.authorWang, Yangangen_US
dc.contributor.authorYang, Jingyuen_US
dc.contributor.editorFu, Hongbo and Ghosh, Abhijeet and Kopf, Johannesen_US
dc.date.accessioned2018-10-07T15:00:14Z
dc.date.available2018-10-07T15:00:14Z
dc.date.issued2018
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.13574
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13574
dc.description.abstractMulti-person pose and shape estimation is very challenging, especially when the persons have close interactions. Existing methods only work well when people are well spaced out in the captured images. However, close interaction among people is very common in real life, which is more challenge due to complex articulation, frequent occlusion and inherent ambiguities. We present a fully-automatic markerless motion capture method to simultaneously estimate 3D poses and shapes of closely interacting people from multi-view sequences. We first predict the 2D joints for each person in an image, and then design a spatio-temporal tracker for multi-person pose tracking based on multi-view videos. Finally, we estimate 3D poses and shapes of all the persons with multi-view constraints using a skinned multi-person linear model (SMPL). Experimental results demonstrate that our method achieves fast but accurate pose and shape estimation results for multi-person close interaction cases. Compared with existing methods, our method does not need pre-segmentation for each person and manual intervention, which greatly reduces the complexity of the system including time complexity and system processing complexity.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.4.8 [Computer Graphics]
dc.subjectScene Analysis
dc.subjectShape
dc.subjectMotion
dc.titleShape and Pose Estimation for Closely Interacting Persons Using Multi-view Imagesen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheaders3D Modeling
dc.description.volume37
dc.description.number7
dc.identifier.doi10.1111/cgf.13574
dc.identifier.pages361-371


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  • 37-Issue 7
    Pacific Graphics 2018 - Symposium Proceedings

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