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    Closed-Form Hierarchical Finite Element Models for Part-Based Object Detection

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    137-144.pdf (6.137Mb)
    Date
    2013
    Author
    Rak, Marko
    Engel, Karin
    Tönnies, Klaus D.
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    Abstract
    In this work we address part-based object detection under variability of part shapes and spatial relations. Our approach bases on the hierarchical finite element modeling concept of Engel and Tönnies [ET09a, ET09b]. They model object parts by elastic materials, which adapt to image structures via image-derived forces. Spatial part relations are realized through additional layers of elastic material forming an elastic hierarchy. We present a closed-form solution to this concept, reformulating the hierarchical optimization problem into the optimization of a non-hierarchical finite element model. This allows us to apply standard finite element techniques to hierarchical problems and to provide an efficient framework for part-based object detection. We demonstrate our approach at the example of lumbar column detection in magnetic resonance imaging on a data set of 49 subjects. Given a rough model initialization, our approach solved the detection problem reliably in 45 out of 49 cases, showing computation times of only a few seconds per subject.
    BibTeX
    @inproceedings {10.2312:PE.VMV.VMV13.137-144,
    booktitle = {Vision, Modeling & Visualization},
    editor = {Michael Bronstein and Jean Favre and Kai Hormann},
    title = {{Closed-Form Hierarchical Finite Element Models for Part-Based Object Detection}},
    author = {Rak, Marko and Engel, Karin and Tönnies, Klaus D.},
    year = {2013},
    publisher = {The Eurographics Association},
    ISBN = {978-3-905674-51-4},
    DOI = {10.2312/PE.VMV.VMV13.137-144}
    }
    URI
    http://dx.doi.org/10.2312/PE.VMV.VMV13.137-144
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA