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    New Techniques for Hand Pose Estimation Based on Kinect Depth Data

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    Date
    2014
    Author
    Hummel, Simon
    Haefner, Victor
    Haefner, Polina
    Ovtcharova, Jivka
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    Abstract
    In this paper we present new techniques for extension and improvement of approaches to markerless 3D hand pose estimation: A new algorithm for finger segmentation in point clouds of hands is presented which makes use of the narrow and flexible shape of the fingers. The kinematic of a 3D hand model gets aligned to the geodesic paths of the fingers which provides a very natural configuration of the model. Therefore a new technique for optimization of those geodesic paths is introduced. Another benefit of this system is, that it's only data resource is the depth stream of a Kinect. So no additional hardware, markers or training data is needed. A first implementation of our approach provides a proof for the new concepts and looks promising for further investigation.
    BibTeX
    @inproceedings {10.2312:eurovr.20141355,
    booktitle = {EuroVR 2014 - Conference and Exhibition of the European Association of Virtual and Augmented Reality},
    editor = {Jerome Perret and Valter Basso and Francesco Ferrise and Kaj Helin and Vincent Lepetit and James Ritchie and Christoph Runde and Mascha van der Voort and Gabriel Zachmann},
    title = {{New Techniques for Hand Pose Estimation Based on Kinect Depth Data}},
    author = {Hummel, Simon and Haefner, Victor and Haefner, Polina and Ovtcharova, Jivka},
    year = {2014},
    publisher = {The Eurographics Association},
    ISBN = {978-3-905674-76-7},
    DOI = {10.2312/eurovr.20141355}
    }
    URI
    http://dx.doi.org/10.2312/eurovr.20141355
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    Eurographics Association copyright © 2013 - 2022 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
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