Occlusion Aware Hand Pose Recovery from Sequences of Depth Images

@article{Madadi2017OcclusionAH,
  title={Occlusion Aware Hand Pose Recovery from Sequences of Depth Images},
  author={Meysam Madadi and Sergio Escalera and Alex Carruesco and Carlos And{\'u}jar and Xavier Bar{\'o} and Jordi Gonz{\`a}lez},
  journal={2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017)},
  year={2017},
  pages={230-237}
}
State-of-the-art approaches on hand pose estimation from depth images have reported promising results under quite controlled considerations. In this paper we propose a two-step pipeline for recovering the hand pose from a sequence of depth images. The pipeline has been designed to deal with images taken from any viewpoint and exhibiting a high degree of finger occlusion. In a first step we initialize the hand pose using a part-based model, fitting a set of hand components in the depth images… CONTINUE READING

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