Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition

Andre Neyra-Gutierrez; Pedro Shiguihara-Juarez

doi:10.1109/INTERCON50315.2020.9220243

Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition

Andre Neyra-Gutierrez, Pedro Shiguihara-Juarez

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

4 Citas (Scopus)

Resumen

In peruvian sign language (PSL), recognition of static gestures has been proposed earlier. However, to state a conversation using sign language, it is also necessary to employ dynamic gestures. We propose a method to extract a feature vector for dynamic gestures of PSL. We collect a dataset with 288 video sequences of words related to dynamic gestures and we state a workflow to process the keypoints of the hands, obtaining a feature vector for each video sequence with the support of a video summarization technique. We employ 9 neural networks to test the method, achieving an average accuracy ranging from 80% and 90%, using 10 fold cross-validation.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781728193779
DOI	https://doi.org/10.1109/INTERCON50315.2020.9220243
Estado	Publicada - set. 2020
Publicado de forma externa	Sí
Evento	27th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020 - Virtual, Lima, Perú Duración: 3 set. 2020 → 5 set. 2020

Serie de la publicación

Nombre	Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020

Conferencia

Conferencia	27th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020
País/Territorio	Perú
Ciudad	Virtual, Lima
Período	3/09/20 → 5/09/20

ODS de las Naciones Unidas

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10.1109/INTERCON50315.2020.9220243

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Neyra-Gutierrez, A., & Shiguihara-Juarez, P. (2020). Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition. En Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020 [9220243] (Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INTERCON50315.2020.9220243

Neyra-Gutierrez, Andre ; Shiguihara-Juarez, Pedro. / Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition. Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020. Institute of Electrical and Electronics Engineers Inc., 2020. (Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020).

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title = "Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition",

abstract = "In peruvian sign language (PSL), recognition of static gestures has been proposed earlier. However, to state a conversation using sign language, it is also necessary to employ dynamic gestures. We propose a method to extract a feature vector for dynamic gestures of PSL. We collect a dataset with 288 video sequences of words related to dynamic gestures and we state a workflow to process the keypoints of the hands, obtaining a feature vector for each video sequence with the support of a video summarization technique. We employ 9 neural networks to test the method, achieving an average accuracy ranging from 80% and 90%, using 10 fold cross-validation.",

keywords = "Dynamic Gestures, Feature Extraction, Peruvian Signal Language, Sign Language Recognition, Video Summarization",

author = "Andre Neyra-Gutierrez and Pedro Shiguihara-Juarez",

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Neyra-Gutierrez, A & Shiguihara-Juarez, P 2020, Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition. En Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020., 9220243, Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020, Institute of Electrical and Electronics Engineers Inc., 27th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020, Virtual, Lima, Perú, 3/09/20. https://doi.org/10.1109/INTERCON50315.2020.9220243

Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition. / Neyra-Gutierrez, Andre; Shiguihara-Juarez, Pedro.

Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9220243 (Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020).

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition

AU - Neyra-Gutierrez, Andre

AU - Shiguihara-Juarez, Pedro

PY - 2020/9

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N2 - In peruvian sign language (PSL), recognition of static gestures has been proposed earlier. However, to state a conversation using sign language, it is also necessary to employ dynamic gestures. We propose a method to extract a feature vector for dynamic gestures of PSL. We collect a dataset with 288 video sequences of words related to dynamic gestures and we state a workflow to process the keypoints of the hands, obtaining a feature vector for each video sequence with the support of a video summarization technique. We employ 9 neural networks to test the method, achieving an average accuracy ranging from 80% and 90%, using 10 fold cross-validation.

AB - In peruvian sign language (PSL), recognition of static gestures has been proposed earlier. However, to state a conversation using sign language, it is also necessary to employ dynamic gestures. We propose a method to extract a feature vector for dynamic gestures of PSL. We collect a dataset with 288 video sequences of words related to dynamic gestures and we state a workflow to process the keypoints of the hands, obtaining a feature vector for each video sequence with the support of a video summarization technique. We employ 9 neural networks to test the method, achieving an average accuracy ranging from 80% and 90%, using 10 fold cross-validation.

KW - Dynamic Gestures

KW - Feature Extraction

KW - Peruvian Signal Language

KW - Sign Language Recognition

KW - Video Summarization

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Neyra-Gutierrez A, Shiguihara-Juarez P. Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition. En Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9220243. (Proceedings of the 2020 IEEE 27th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2020). doi: 10.1109/INTERCON50315.2020.9220243

Feature Extraction with Video Summarization of Dynamic Gestures for Peruvian Sign Language Recognition

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