Face Alignment Using K-Cluster Regression Forests With Weighted Splitting

@article{Kowalski2016FaceAU,
  title={Face Alignment Using K-Cluster Regression Forests With Weighted Splitting},
  author={Marek Kowalski and Jacek Naruniec},
  journal={IEEE Signal Processing Letters},
  year={2016},
  volume={23},
  pages={1567-1571}
}
In this letter, we present a face alignment pipeline based on two novel methods: weighted splitting for K-cluster Regression Forests (KRF) and three-dimensional Affine Pose Regression (3D-APR) for face shape initialization. Our face alignment method is based on the Local Binary Feature (LBF) framework, where instead of standard regression forests and pixel difference features used in the original method, we use our K-Cluster Regression Forests with Weighted Splitting (KRFWS) and Pyramid… CONTINUE READING
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