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A Nonlinear Discriminative Approach to AAM Fitting

Jason M. Saragih, Roland Göcke
ICCV 2007 pp. 1-8
doi:10.1109/ICCV.2007.4409106 /iccv/2007/saragih2007iccv-nonlinear/

Abstract

The Active Appearance Model (AAM) is a powerful generative method for modeling and registering deformable visual objects. Most methods for AAM fitting utilize a linear parameter update model in an iterative framework. Despite its popularity, the scope of

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Cite

Text

Saragih and Göcke. "A Nonlinear Discriminative Approach to AAM Fitting." IEEE/CVF International Conference on Computer Vision, 2007. doi:10.1109/ICCV.2007.4409106

Markdown

[Saragih and Göcke. "A Nonlinear Discriminative Approach to AAM Fitting." IEEE/CVF International Conference on Computer Vision, 2007.](https://mlanthology.org/iccv/2007/saragih2007iccv-nonlinear/) doi:10.1109/ICCV.2007.4409106

BibTeX

@inproceedings{saragih2007iccv-nonlinear,
  title     = {{A Nonlinear Discriminative Approach to AAM Fitting}},
  author    = {Saragih, Jason M. and Göcke, Roland},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {2007},
  pages     = {1-8},
  doi       = {10.1109/ICCV.2007.4409106},
  url       = {https://mlanthology.org/iccv/2007/saragih2007iccv-nonlinear/}
}