Sign Language Numeral Gestures Recognition Using Convolutional Neural Network

被引：10
|
作者：
Gruber, Ivan [1 ,2 ]
Ryumin, Dmitry [3 ]
Hruz, Marek [1 ,2 ]
Karpov, Alexey [3 ]
机构：
[1] UWB, Dept Cybernet, Fac Appl Sci, Plzen, Czech Republic
[2] UWB, Fac Appl Sci, NTIS, Plzen, Czech Republic
[3] SPIIRAS, St Petersburg, Russia
来源：
INTERACTIVE COLLABORATIVE ROBOTICS, ICR 2018 | 2018年 / 11097卷
关键词：
Sign language; Image recognition; Classification; Neural network; Assistive robot; Computer vision;
D O I：
10.1007/978-3-319-99582-3_8
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents usage of convolutional neural network for classification of sign language numeral gestures. For requirements of this research, we created a new dataset of these gestures. The dataset was recorded via Kinect v2 device and it consists of recordings of 18 different people. Only depth data-stream was used in our research. For a classification task, there was utilized classic VGG16 architecture and its results were compared with chosen baseline method and other tested architectures. Our experiment on classification showed the great potential of neural networks for this task. We reached recognition accuracy 86.45%, which is by more than 34% better result than chosen baseline method.
引用
收藏
页码：70 / 77
页数：8
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