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




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



    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.


    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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