Intrinsic Shape Matching by Planned Landmark Sampling

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dc.contributor.authorTevs, Arten_US
dc.contributor.authorBerner, Alexanderen_US
dc.contributor.authorWand, Michaelen_US
dc.contributor.authorIhrke, Ivoen_US
dc.contributor.authorSeidel, Hans-Peteren_US
dc.contributor.editorM. Chen and O. Deussenen_US
dc.date.accessioned2015-02-27T10:23:24Z
dc.date.available2015-02-27T10:23:24Z
dc.date.issued2011en_US
dc.description.abstractRecently, the problem of intrinsic shape matching has received a lot of attention. A number of algorithms have been proposed, among which random-sampling-based techniques have been particularly successful due to their generality and efficiency. We introduce a new sampling-based shape matching algorithm that uses a planning step to find optimized "landmark" points. These points are matched first in order to maximize the information gained and thus minimize the sampling costs. Our approach makes three main contributions: First, the new technique leads to a significant improvement in performance, which we demonstrate on a number of benchmark scenarios. Second, our technique does not require any keypoint detection. This is often a significant limitation for models that do not show sufficient surface features. Third, we examine the actual numerical degrees of freedom of the matching problem for a given piece of geometry. In contrast to previous results, our estimates take into account unprecise geodesics and potentially numerically unfavorable geometry of general topology, giving a more realistic complexity estimate.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.identifier.doi10.1111/j.1467-8659.2011.01879.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2011.01879.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleIntrinsic Shape Matching by Planned Landmark Samplingen_US
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