sign-lang@LREC Anthology

An HMM Approach with Inherent Model Selection for Sign Language and Gesture Recognition

Tornay, Sandrine | Aran, Oya | Magimai Doss, Mathew


Volume:
Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020)
Venue:
Marseille, France
Date:
11 to 16 May 2020
Pages:
6049–6056
Publisher:
European Language Resources Association (ELRA)
License:
CC BY-NC 4.0
ACL ID:
2020.lrec-1.741
ISBN:
979-10-95546-34-4

Content Categories

Projects:
SMILE
Corpora:
BosphorusSign - Health, Chalearn14 Dataset, Kinect DGS 40

Abstract

HMMs have been the one of the first models to be applied for sign recognition and have become the baseline models due to their success in modeling sequential and multivariate data. Despite the extensive use of HMMs for sign recognition, determining the HMM structure has still remained as a challenge, especially when the number of signs to be modeled is high. In this work, we present a continuous HMM framework for modeling and recognizing isolated signs, which inherently performs model selection to optimize the number of states for each sign separately during recognition. Our experiments on three different datasets, namely, German sign language DGS dataset, Turkish sign language HospiSign dataset and Chalearn14 dataset show that the proposed approach achieves better sign language or gesture recognition systems in comparison to the approach of selecting or presetting the number of HMM states based on k-means, and yields systems that perform competitive to the case where the number of states are determined based on the test set performance.

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@inproceedings{tornay-etal-2020-hmm:lrec,
  author    = {Tornay, Sandrine and Aran, Oya and Magimai Doss, Mathew},
  title     = {An {HMM} Approach with Inherent Model Selection for Sign Language and Gesture Recognition},
  pages     = {6049--6056},
  editor    = {Calzolari, Nicoletta and Fr{\'e}d{\'e}ric B{\'e}chet and Blache, Philippe and Choukri, Khalid and Cieri, Christopher and Declerck, Thierry and Goggi, Sara and Isahara, Hitoshi and Maegaard, Bente and Mariani, Joseph and Mazo, H{\'e}l{\`e}ne and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios},
  booktitle = {12th International Conference on Language Resources and Evaluation ({LREC} 2020)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Marseille, France},
  day       = {11--16},
  month     = may,
  year      = {2020},
  isbn      = {979-10-95546-34-4},
  language  = {english},
  url       = {https://aclanthology.org/2020.lrec-1.741}
}
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