Time-series Clustering with Jointly Learning Deep Representations, Clusters and Temporal Boundaries

@article{Tzirakis2019TimeseriesCW,
  title={Time-series Clustering with Jointly Learning Deep Representations, Clusters and Temporal Boundaries},
  author={Panagiotis Tzirakis and Mihalis A. Nicolaou and Bj{\"o}rn Schuller and Stefanos Zafeiriou},
  journal={2019 14th IEEE International Conference on Automatic Face \& Gesture Recognition (FG 2019)},
  year={2019},
  pages={1-5}
}
Clustering and segmentation of temporal data is an important task across several fields, with prominent applications in computer vision and machine learning such as face and gesture segmentation. [] Key Method In this paper, we propose the first methodology that simultaneously discovers suitable deep representations, as well as clusters and temporal boundaries, with the clustering process providing supervisory cues for updating temporal boundaries and training the proposed deep learning architecture. We…

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