ML Anthology

3D Constrained Local Model for Rigid and Non-Rigid Facial Tracking

Tadas Baltrusaitis, Peter Robinson, Louis-Philippe Morency
CVPR 2012 pp. 2610-2617
doi:10.1109/CVPR.2012.6247980 /cvpr/2012/baltrusaitis2012cvpr-d/

Abstract

We present 3D Constrained Local Model (CLM-Z) for robust facial feature tracking under varying pose. Our approach integrates both depth and intensity information in a common framework. We show the benefit of our CLM-Z method in both accuracy and convergence rates over regular CLM formulation through experiments on publicly available datasets. Additionally, we demonstrate a way to combine a rigid head pose tracker with CLM-Z that benefits rigid head tracking. We show better performance than the current state-of-the-art approaches in head pose tracking with our extension of the generalised adaptive view-based appearance model (GAVAM).

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Cite

Text

Baltrusaitis et al. "3D Constrained Local Model for Rigid and Non-Rigid Facial Tracking." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012. doi:10.1109/CVPR.2012.6247980

Markdown

[Baltrusaitis et al. "3D Constrained Local Model for Rigid and Non-Rigid Facial Tracking." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012.](https://mlanthology.org/cvpr/2012/baltrusaitis2012cvpr-d/) doi:10.1109/CVPR.2012.6247980

BibTeX

@inproceedings{baltrusaitis2012cvpr-d,
  title     = {{3D Constrained Local Model for Rigid and Non-Rigid Facial Tracking}},
  author    = {Baltrusaitis, Tadas and Robinson, Peter and Morency, Louis-Philippe},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2012},
  pages     = {2610-2617},
  doi       = {10.1109/CVPR.2012.6247980},
  url       = {https://mlanthology.org/cvpr/2012/baltrusaitis2012cvpr-d/}
}