Spatial-Temporal Graph Convolutional Networks for Sign Language Recognition

被引：29

作者：

de Amorim, Cleison Correia ^{[1
]}

Macedo, David ^{[1
]}

Zanchettin, Cleber ^{[1
]}

机构：

[1] Univ Fed Pernambuco, Ctr Informat, BR-50740560 Recife, PE, Brazil

来源：

ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2019: WORKSHOP AND SPECIAL SESSIONS | 2019年 / 11731卷

关键词：

Sign language; Convolutional Neural Network; Spatial Temporal Graph;

D O I：

10.1007/978-3-030-30493-5_59

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The recognition of sign language is a challenging task with an important role in society to facilitate the communication of deaf persons. We propose a new approach of Spatial-Temporal Graph Convolutional Network for sign language recognition based on the human skeletal movements. The method uses graphs to capture the dynamics of the signs in two dimensions, spatial and temporal, considering the complex aspects of the language. Additionally, we present a new dataset of human skeletons for sign language based on ASLLVD to contribute to future related studies.

引用

页码：646 / 657

页数：12

共 50 条

[1] Isolated Sign Language Recognition with Multi-Scale Spatial-Temporal Graph Convolutional Networks
Vazquez-Enriquez, Manuel
Alba-Castro, Jose L.
Docio-Fernandez, Laura
Rodriguez-Banga, Eduardo
[J]. 2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021, 2021, : 3457 - 3466
[2] Structure-aware sign language recognition with spatial-temporal scene graph
Lin, Shiquan
Xiao, Zhengye
Wang, Lixin
Wan, Xiuan
Ni, Lan
Fang, Yuchun
[J]. INFORMATION PROCESSING & MANAGEMENT, 2024, 61 (06)
[3] Continuous Sign Language Recognition Based on Spatial-Temporal Graph Attention Network
Guo, Qi
Zhang, Shujun
Li, Hui
[J]. CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2023, 134 (03): : 1653 - 1670
[4] SPATIO-TEMPORAL GRAPH CONVOLUTIONAL NETWORKS FOR CONTINUOUS SIGN LANGUAGE RECOGNITION
Parelli, Maria
Papadimitriou, Katerina
Potamianos, Gerasimos
Pavlakos, Georgios
Maragos, Petros
[J]. 2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2022, : 8457 - 8461
[5] Video Action Recognition by Combining Spatial-Temporal Cues with Graph Convolutional Networks
Li, Tao
Xiong, Wenjun
Zhang, Zheng
Pei, Lishen
[J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2023,
[6] Video Action Recognition by Combining Spatial-Temporal Cues with Graph Convolutional Networks
Li, Tao
Xiong, Wenjun
Zhang, Zheng
Pei, Lishen
[J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2023,
[7] Spatial-temporal attention with graph and general neural network-based sign language recognition
Miah, Abu Saleh Musa
Hasan, Md. Al Mehedi
Okuyama, Yuichi
Tomioka, Yoichi
Shin, Jungpil
[J]. PATTERN ANALYSIS AND APPLICATIONS, 2024, 27 (02)
[8] Spatial-temporal correlation graph convolutional networks for traffic forecasting
Huang, Ru
Chen, Zijian
Zhai, Guangtao
He, Jianhua
Chu, Xiaoli
[J]. IET INTELLIGENT TRANSPORT SYSTEMS, 2023, 17 (07) : 1380 - 1394
[9] Railway Delay Prediction with Spatial-Temporal Graph Convolutional Networks
Heglund, Jacob S. W.
Taleongpong, Panukorn
Hu, Simon
Tran, Huy T.
[J]. 2020 IEEE 23RD INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2020,
[10] Spatial-Temporal Enhanced Network for Continuous Sign Language Recognition
Yin, Wenjie
Hou, Yonghong
Guo, Zihui
Liu, Kailin
[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2024, 34 (03) : 1684 - 1695

← 1 2 3 4 5 →