Human shape correspondence with automatically predicted landmarks

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DOIResolve DOI: http://doi.org/10.1007/s00138-011-0361-9
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TypeArticle
Journal titleMachine Vision and Applications
ISSN0932-8092
Volume23
Issue4
Pages821830; # of pages: 10
Subjectshape correspondence; anthropometric landmarks; human models; landmark prediction
AbstractWe consider the problem of computing accurate point-to-point correspondences among a set of human bodies in similar posture using a landmark-free approach. The approach learns the locations of the anthropometric landmarks present in a database of human models in similar postures and uses this knowledge to automatically predict the locations of these anthropometric landmarks on a newly available scan. The predicted landmarks are then used to compute point-to-point correspondences between a template model and the newly available scan. This study conducts a large-scale evaluation to examine the accuracy of the computed correspondences. Furthermore, we show that the correspondences are accurate enough for the application of motion transfer.
Publication date
PublisherSpringer
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedYes
NPARC number21268090
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Record identifierb5ac8679-e8c2-4e3d-95ce-d8ad0bbe9343
Record created2013-04-09
Record modified2016-05-09
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