Articulated and Generalized Gaussian Kernel Correlation for Human Pose Estimation

@article{Ding2016ArticulatedAG,
  title={Articulated and Generalized Gaussian Kernel Correlation for Human Pose Estimation},
  author={Meng Ding and Guoliang Fan},
  journal={IEEE Transactions on Image Processing},
  year={2016},
  volume={25},
  pages={776-789}
}
In this paper, we propose an articulated and generalized Gaussian kernel correlation (GKC)-based framework for human pose estimation. We first derive a unified GKC representation that generalizes the previous sum of Gaussians (SoG)-based methods for the similarity measure between a template and an observation both of which are represented by various SoG variants. Then, we develop an articulated GKC (AGKC) by integrating a kinematic skeleton in a multivariate SoG template that supports subject… CONTINUE READING
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