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김광인

Kim, Kwang In
Machine Learning and Vision Lab.
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dc.citation.conferencePlace US -
dc.citation.conferencePlace Providence, RI -
dc.citation.endPage 1877 -
dc.citation.startPage 1870 -
dc.citation.title IEEE Conference on Computer Vision and Pattern Recognition -
dc.contributor.author Elhayek, A. -
dc.contributor.author Stoll, C. -
dc.contributor.author Hasler, N. -
dc.contributor.author Kim, K.I. -
dc.contributor.author Seidel, H.-P. -
dc.contributor.author Theobalt, C. -
dc.date.accessioned 2023-12-20T02:06:52Z -
dc.date.available 2023-12-20T02:06:52Z -
dc.date.created 2019-02-27 -
dc.date.issued 2012-06-16 -
dc.description.abstract We present a new spatio-temporal method for markerless motion capture. We reconstruct the pose and motion of a character from a multi-view video sequence without requiring the cameras to be synchronized and without aligning captured frames in time. By formulating the model-to-image similarity measure as a temporally continuous functional, we are also able to reconstruct motion in much higher temporal detail than was possible with previous synchronized approaches. By purposefully running cameras unsynchronized we can capture even very fast motion at speeds that off-the-shelf but high quality cameras provide. © 2012 IEEE. -
dc.identifier.bibliographicCitation IEEE Conference on Computer Vision and Pattern Recognition, pp.1870 - 1877 -
dc.identifier.doi 10.1109/CVPR.2012.6247886 -
dc.identifier.issn 1063-6919 -
dc.identifier.scopusid 2-s2.0-84866716346 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/32630 -
dc.identifier.url https://ieeexplore.ieee.org/document/6247886 -
dc.language 영어 -
dc.publisher IEEE -
dc.title Spatio-temporal motion tracking with unsynchronized cameras -
dc.type Conference Paper -
dc.date.conferenceDate 2012-06-16 -

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