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Local shape blending using coherent weighted regions

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Abstract

We present a novel local shape blending method that maps a sparse configuration of facial markers captured from an actor onto target models. The advantage of local shape blending methods is that, given a small set of key shapes for each local region, their combination can generate various facial expressions. However, they have the common problem that they use the pre-determined (fixed) regions and compute the combination of local key shapes for each region independently of each other. So, they have a risk of breaking natural correlations between the regions. We present a stochastic method of computing the regions and the blending weight vectors simultaneously. To do so, we formulate local shape blending as a problem of finding an optimal distribution of blending weight vectors of all control points in MAP–MRF framework.

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Authors and Affiliations

  1. Department of Media Technology, Sogang University, Seoul, South Korea

    Kyung-Gun Na & Moon-Ryul Jung

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  1. Kyung-Gun Na
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  2. Moon-Ryul Jung
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Correspondence to Moon-Ryul Jung.

Additional information

This work was supported by the Sogang University Research Grant of 2010.

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Na, KG., Jung, MR. Local shape blending using coherent weighted regions. Vis Comput 27, 575–584 (2011). https://doi.org/10.1007/s00371-011-0591-x

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