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    Symmetry-aware human shape correspondence using skeleton 
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    Symmetry-aware human shape correspondence using skeleton

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    Published version
    Embargoed until: 2100-01-01
    Reason: Publisher won't allow use of book materials
    Volume
    9516
    Pagination
    632 - 641
    ISBN-13
    9783319276700
    DOI
    10.1007/978-3-319-27671-7_53
    ISSN
    0302-9743
    Metadata
    Show full item record
    Abstract
    © Springer International Publishing Switzerland 2016. In this paper, we propose a symmetry-aware human shape correspondence extraction method. We address the symmetric flip problem which exists in establishing correspondences for intrinsically symmetric models and improve the accuracy of the final corresponding pairs. To achieve this goal, we extended the state-of-the-art approach by using skeleton information to further remove symmetric flipped shape correspondences. Traditional approaches that only rely on surface geometry information can hardly discriminate surface points which are symmetric. With the appearance of inexpensive RGB-D camera, such as Kinect, skeleton information can be easily obtained along with mesh. Therefore, after the initial correspondences are achieved, we extend the candidate sets for each point on the template, followed by making use of skeleton to remove the symmetric flipped false candidates. In the remaining candidates, final correspondences are achieved by choosing those with minimum geodesic distortion from base vertex set, which is formed by sampling on the mesh. Experiments demonstrate that the proposed method can effectively remove all the symmetric flipped candidates. Moreover, the final correspondence pair is more accurate than those of the state of the arts.
    Authors
    Xu, Z; Zhang, Q
    URI
    http://qmro.qmul.ac.uk/xmlui/handle/123456789/13697
    Collections
    • Electronic Engineering and Computer Science [2362]
    Licence information
    “The final publication is available at http://link.springer.com/chapter/10.1007/978-3-319-27671-7_53”
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