Combining Marker-based Mocap and RGB-D Camera for Acquiring High-fidelity Hand Motion Data

dc.contributor.authorZhao, Wenpingen_US
dc.contributor.authorChai, Jinxiangen_US
dc.contributor.authorXu, Ying-Qingen_US
dc.contributor.editorJehee Lee and Paul Kryen_US
dc.date.accessioned2014-01-29T08:00:39Z
dc.date.available2014-01-29T08:00:39Z
dc.date.issued2012en_US
dc.description.abstractMotion capture data has been pivotal to the success of creating realistic animation for human characters. There are a number of public full-body motion databases available, but large and heterogeneous databases for hand articulations are not available. In this paper, we introduce a novel acquisition framework for acquiring a wide range of high-fidelity hand motion data. Our key idea is to leverage marker position data recorded by a twelvecamera optical motion capture system and RGB/Depth data obtained from a single Microsoft Kinect camera. We formulate the hand motion capture problem in a nonlinear optimization framework by maximizing consistency between the reconstructed motion and observed measurement. We introduce an efficient optimization technique to estimate the optimal hand pose that best matches observed data.We have demonstrated the power and effectiveness of our system by capturing a wide variety of delicate hand articulations, even in case of significant self-occlusion.en_US
dc.description.seriesinformationEurographics/ ACM SIGGRAPH Symposium on Computer Animationen_US
dc.identifier.isbn978-3-905674-37-8en_US
dc.identifier.issn1727-5288en_US
dc.identifier.urihttps://doi.org/10.2312/SCA/SCA12/033-042en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.7 [Computer Graphics]en_US
dc.subjectThree Dimensional Graphics and Realismen_US
dc.subjectAnimationen_US
dc.titleCombining Marker-based Mocap and RGB-D Camera for Acquiring High-fidelity Hand Motion Dataen_US
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