Multi-View Constrained Local Models for Large Head Angle Facial Tracking

Rajamanoharan, Georgia; Cootes, Timothy F.

doi:10.1109/ICCVW.2015.128

Multi-View Constrained Local Models for Large Head Angle Facial Tracking

Georgia Rajamanoharan, Timothy F. Cootes

ICCVW 2015 pp. 971-978

doi:10.1109/ICCVW.2015.128 /iccvw/2015/rajamanoharan2015iccvw-multiview/

Abstract

We propose Multi-View Constrained Local Models - a simple but effective technique for improving facial point detection under large head angles, such as in a car driving setting. Our approach combines a global shape model with separate sets of response maps targeted at different head angles, indexed on the shape model parameters. We explore shape-space division strategies and show that, as well as outperforming the traditional method, our approach also provides a marked speed-up which demonstrates the suitability of this technique for real-time face tracking.

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Cite

Text

Rajamanoharan and Cootes. "Multi-View Constrained Local Models for Large Head Angle Facial Tracking." IEEE/CVF International Conference on Computer Vision Workshops, 2015. doi:10.1109/ICCVW.2015.128

Markdown

[Rajamanoharan and Cootes. "Multi-View Constrained Local Models for Large Head Angle Facial Tracking." IEEE/CVF International Conference on Computer Vision Workshops, 2015.](https://mlanthology.org/iccvw/2015/rajamanoharan2015iccvw-multiview/) doi:10.1109/ICCVW.2015.128

BibTeX

@inproceedings{rajamanoharan2015iccvw-multiview,
  title     = {{Multi-View Constrained Local Models for Large Head Angle Facial Tracking}},
  author    = {Rajamanoharan, Georgia and Cootes, Timothy F.},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2015},
  pages     = {971-978},
  doi       = {10.1109/ICCVW.2015.128},
  url       = {https://mlanthology.org/iccvw/2015/rajamanoharan2015iccvw-multiview/}
}