Automatic Registration for Articulated Shapes

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dc.contributor.authorChang, Willen_US
dc.contributor.authorZwicker, Matthiasen_US
dc.date.accessioned2015-02-21T17:32:31Z
dc.date.available2015-02-21T17:32:31Z
dc.date.issued2008en_US
dc.description.abstractWe present an unsupervised algorithm for aligning a pair of shapes in the presence of significant articulated motion and missing data, while assuming no knowledge of a template, user-placed markers, segmentation, or the skeletal structure of the shape. We explicitly sample the motion, which gives a priori the set of possible rigid transformations between parts of the shapes. This transforms the problem into a discrete labeling problem, where the goal is to find an optimal assignment of transformations for aligning the shapes. We then apply graph cuts to optimize a novel cost function, which encodes a preference for a consistent motion assignment from both source to target and target to source. We demonstrate the robustness of our method by aligning several synthetic and real-world datasets.en_US
dc.description.number5en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume27en_US
dc.identifier.doi10.1111/j.1467-8659.2008.01286.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages1459-1468en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2008.01286.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titleAutomatic Registration for Articulated Shapesen_US
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27-Issue 5
SGP08: Eurographics Symposium on Geometry Processing