TY - GEN
T1 - Data collection of 3D spatial features of gestures from static peruvian sign language alphabet for sign language recognition
AU - Nurena-Jara, Roberto
AU - Ramos-Carrion, Cristopher
AU - Shiguihara-Juarez, Pedro
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/21
Y1 - 2020/10/21
N2 - Peruvian Sign Language Recognition (PSL) is approached as a classification problem. Previous work has employed 2D features from the position of hands to tackle this problem. In this paper, we propose a method to construct a dataset consisting of 3D spatial positions of static gestures from the PSL alphabet, using the HTC Vive device and a well-known technique to extract 21 keypoints from the hand to obtain a feature vector. A dataset of 35, 400 instances of gestures for PSL was constructed and a novel way to extract data was stated. To validate the appropriateness of this dataset, a comparison of four baselines classifiers in the Peruvian Sign Language Recognition (PSLR) task was stated, achieving 99.32% in the average in terms of F1 measure in the best case.
AB - Peruvian Sign Language Recognition (PSL) is approached as a classification problem. Previous work has employed 2D features from the position of hands to tackle this problem. In this paper, we propose a method to construct a dataset consisting of 3D spatial positions of static gestures from the PSL alphabet, using the HTC Vive device and a well-known technique to extract 21 keypoints from the hand to obtain a feature vector. A dataset of 35, 400 instances of gestures for PSL was constructed and a novel way to extract data was stated. To validate the appropriateness of this dataset, a comparison of four baselines classifiers in the Peruvian Sign Language Recognition (PSLR) task was stated, achieving 99.32% in the average in terms of F1 measure in the best case.
KW - Peruvian sign language
KW - gesture recognition
KW - sign language recognition
UR - https://www.scopus.com/pages/publications/85097807930
U2 - 10.1109/EIRCON51178.2020.9254019
DO - 10.1109/EIRCON51178.2020.9254019
M3 - Contribución a la conferencia
AN - SCOPUS:85097807930
T3 - Proceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020
BT - Proceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Engineering International Research Conference, EIRCON 2020
Y2 - 21 October 2020 through 23 October 2020
ER -