Δημοσιεύσεις
2022
Sapountzaki, Galini; Efthimiou, Eleni; Fotinea, Stavroula-Evita; Papadimitriou, Katerina; Potamianos, Gerasimos
3D GREEK SIGN LANGUAGE CLASSIFIERS AS A LEARNING OBJECT IN THE SL-REDU ONLINE EDUCATION PLATFORM Proceedings Article
In: EDULEARN22 Proceedings, pp. 6146–6153, IATED 2022.
@inproceedings{sapountzaki20223d,
title = {3D GREEK SIGN LANGUAGE CLASSIFIERS AS A LEARNING OBJECT IN THE SL-REDU ONLINE EDUCATION PLATFORM},
author = {Galini Sapountzaki and Eleni Efthimiou and Stavroula-Evita Fotinea and Katerina Papadimitriou and Gerasimos Potamianos},
year = {2022},
date = {2022-01-01},
booktitle = {EDULEARN22 Proceedings},
pages = {6146--6153},
organization = {IATED},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Papadimitriou, Katerina; Potamianos, Gerasimos; Sapountzaki, Galini; Goulas, Theodoros; Efthimiou, Eleni; Fotinea, Stavroula-Evita; Maragos, Petros
Greek Sign Language Recognition for the SL-ReDu Learning Platform Proceedings Article
In: Proceedings of the 7th International Workshop on Sign Language Translation and Avatar Technology: The Junction of the Visual and the Textual: Challenges and Perspectives, pp. 79–84, 2022.
@inproceedings{papadimitriou2022greek,
title = {Greek Sign Language Recognition for the SL-ReDu Learning Platform},
author = {Katerina Papadimitriou and Gerasimos Potamianos and Galini Sapountzaki and Theodoros Goulas and Eleni Efthimiou and Stavroula-Evita Fotinea and Petros Maragos},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
booktitle = {Proceedings of the 7th International Workshop on Sign Language Translation and Avatar Technology: The Junction of the Visual and the Textual: Challenges and Perspectives},
pages = {79--84},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2021
Sapountzaki, Galini; Efthimiou, Eleni; Fotinea, Stavroula-Evita; Papadimitriou, Katerina; Potamianos, Gerasimos
Educational material organization in a platform for Greek Sign Language self-monitoring and assessment Proceedings Article
In: Proc. International Conference on Education and New Learning Technologies (EDULEARN) Online Conference, 2021, pp. 3322-3331, 2021.
@inproceedings{Sapountzaki2021,
title = {Educational material organization in a platform for Greek Sign Language self-monitoring and assessment},
author = {Galini Sapountzaki and Eleni Efthimiou and Stavroula-Evita Fotinea and Katerina Papadimitriou and Gerasimos Potamianos},
doi = {10.21125/edulearn.2021.0707},
year = {2021},
date = {2021-12-01},
booktitle = {Proc. International Conference on Education and New Learning Technologies (EDULEARN) Online Conference, 2021},
pages = {3322-3331},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Efthimiou, Eleni; Fotinea, Stavroula-Evita; Flouda, Christina; Goulas, Theodoros; Ametoglou, Gkioulan; Sapountzaki, Galini; Papadimitriou, Katerina; Potamianos, Gerasimos
The SL-ReDu environment for self-monitoring and objective learner assessment in Greek Sign Language Proceedings Article
In: International Conference on Human-Computer Interaction, pp. 72–81, Springer 2021, ISBN: 978-3-030-78094-4.
@inproceedings{efthimiou2021sl,
title = {The SL-ReDu environment for self-monitoring and objective learner assessment in Greek Sign Language},
author = {Eleni Efthimiou and Stavroula-Evita Fotinea and Christina Flouda and Theodoros Goulas and Gkioulan Ametoglou and Galini Sapountzaki and Katerina Papadimitriou and Gerasimos Potamianos},
isbn = {978-3-030-78094-4},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {International Conference on Human-Computer Interaction},
pages = {72--81},
organization = {Springer},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2020
Potamianos, Gerasimos; Papadimitriou, Katerina; Efthimiou, Eleni; Fotinea, Stavroula-Evita; Sapountzaki, Galini; Maragos, Petros
SL-ReDu: Greek sign language recognition for educational applications. Project description and early results Proceedings Article
In: Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments, pp. 1–6, 2020.
@inproceedings{potamianos2020sl,
title = {SL-ReDu: Greek sign language recognition for educational applications. Project description and early results},
author = {Gerasimos Potamianos and Katerina Papadimitriou and Eleni Efthimiou and Stavroula-Evita Fotinea and Galini Sapountzaki and Petros Maragos},
url = {https://www.researchgate.net/publication/342537332_SL-ReDu_greek_sign_language_recognition_for_educational_applications_Project_description_and_early_results},
year = {2020},
date = {2020-01-01},
booktitle = {Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments},
pages = {1--6},
abstract = {We present SL-ReDu, a recently commenced innovative project that aims to exploit deep-learning progress to advance the state-of-the-art in video-based automatic recognition of Greek Sign Language (GSL), while focusing on the use-case of GSL education as a second language. We first briefly overview the project goals, focal areas, and timeline. We then present our initial deep learning-based approach for GSL recognition that employs efficient visual tracking of the signer hands, convolutional neural networks for feature extraction, and attention-based encoder-decoder sequence modeling for sign prediction. Finally, we report experimental results for small-vocabulary, isolated GSL recognition on the single-signer "Polytropon" corpus. To our knowledge, this work constitutes the first application of deep-learning techniques to GSL.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We present SL-ReDu, a recently commenced innovative project that aims to exploit deep-learning progress to advance the state-of-the-art in video-based automatic recognition of Greek Sign Language (GSL), while focusing on the use-case of GSL education as a second language. We first briefly overview the project goals, focal areas, and timeline. We then present our initial deep learning-based approach for GSL recognition that employs efficient visual tracking of the signer hands, convolutional neural networks for feature extraction, and attention-based encoder-decoder sequence modeling for sign prediction. Finally, we report experimental results for small-vocabulary, isolated GSL recognition on the single-signer "Polytropon" corpus. To our knowledge, this work constitutes the first application of deep-learning techniques to GSL.