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Transport Square-root Velocity Framework to Model Latent Space of Human Actions

This code base contains MATLAB source code for the theory on performing elastic registration of Riemannian trajectories.

If this is useful in your work please consider citing our paper:

Anirudh, R., Turaga, P., Su, J., & Srivastava, A., Elastic functional coding of human actions: From vector-fields to latent variables, CVPR 2015. [pdf]

@inproceedings{anirudh2015elastic,
  title={Elastic functional coding of human actions: From vector-fields to latent variables},
  author={Anirudh, Rushil and Turaga, Pavan and Su, Jingyong and Srivastava, Anuj},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={3147--3155},
  year={2015}
}

The Journal version with more manifolds, experiments and analysis is:

Anirudh, R., Turaga, P., Su, J., & Srivastava, A., Elastic functional coding of Riemannian trajectories, in PAMI 2017. [arxiv version]

@article{anirudh2017elastic,
  title={Elastic functional coding of Riemannian trajectories},
  author={Anirudh, Rushil and Turaga, Pavan and Su, Jingyong and Srivastava, Anuj},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={39},
  number={5},
  pages={922--936},
  year={2017},
  publisher={IEEE}
}

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A MATLAB based implementation for the Transport Square-root Velocity Framework to align trajectories on Riemannian manifolds

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