“CageR: from 3D performance capture to cage-based representation” by Thiery, Tierny and Boubekeur

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Title:

    CageR: from 3D performance capture to cage-based representation

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Abstract:


    Modern performance capture systems [de Aguiar et al. 2008] provide high resolution 3D mesh sequences which are becoming critical components for today’s special effects. Unfortunately, such raw sequences have a large memory footprint and are difficult to edit. We propose CageR, a framework based on spatial deformation with cages to construct automatically a compact and editable high level representation of these raw sequences, resulting in high compression factors and allowing easier post processing. In particular, we formulate an automatic cage fitting algorithm embedding a new relaxation strategy based on Maximum Volume and a new regularization method based on sub-spectral analysis. As a result, we use the CageR representation in various applications, including compression, motion transfer and shape space modeling.

References:


    1. de Aguiar, E., Stoll, C., Theobalt, C., Ahmed, N., and Seidel, H. 2008. Performance capture from sparse multi-view video. SIGGRAPH 27.
    2. Goreinov, S., Oaeledets, L., Savostyanov, D., Tyrtyshnikov, E., and Zamarashkin, N. 2010. How to find a good submatrix. Matrix Methods: Theory, Algorithms and Applications, 247.
    3. Ju, T., Schaefer, S., and Warren, J. 2005. Mean value coordinates for closed triangular meshes. SIGGRAPH 24, 3, 561–566.


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