Invariant features for 3-D gesture recognition

@inproceedings{Campbell1996InvariantFF,
  title={Invariant features for 3-D gesture recognition},
  author={Lee W. Campbell and David A. Becker and Ali Azarbayejani and Aaron F. Bobick and Alex Pentland},
  booktitle={FG},
  year={1996}
}
Ten different feature vectors are tested in a gesture recognition task which utilizes 3D data gathered in real-time from stereo video cameras, and HMMs for learning and recognition of gestures. Results indicate velocity features are superior to positional features, and partial rotational invariance is sufficient for good performance. 
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