Corpus ID: 237266730

Classifying In-Place Gestures with End-to-End Point Cloud Learning

@article{Zhao2021ClassifyingIG,
  title={Classifying In-Place Gestures with End-to-End Point Cloud Learning},
  author={Lizhi Zhao and Xuequan Lu and Min Zhao and Meili Wang},
  journal={ArXiv},
  year={2021},
  volume={abs/2108.09639}
}
Walking in place for moving through virtual environments has attracted noticeable attention recently. Recent attempts focused on training a classifier to recognize certain patterns of gestures (e.g., standing, walking, etc) with the use of neural networks like CNN or LSTM. Nevertheless, they often consider very few types of gestures and/or induce less desired latency in virtual environments. In this paper, we propose a novel framework for accurate and efficient classification of in-place… Expand

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