PIEFA: Personalized Incremental and Ensemble Face Alignment

@article{Peng2015PIEFAPI,
  title={PIEFA: Personalized Incremental and Ensemble Face Alignment},
  author={Xi Peng and Shaoting Zhang and Yu Kyung Yang and Dimitris N. Metaxas},
  journal={2015 IEEE International Conference on Computer Vision (ICCV)},
  year={2015},
  pages={3880-3888}
}
Face alignment, especially on real-time or large-scale sequential images, is a challenging task with broad applications. Both generic and joint alignment approaches have been proposed with varying degrees of success. However, many generic methods are heavily sensitive to initializations and usually rely on offline-trained static models, which limit their performance on sequential images with extensive variations. On the other hand, joint methods are restricted to offline applications, since… CONTINUE READING
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