Method for sign language recognition based on Kinect

QIAN Chenghui; SHAO Jingya; XIA Tao; LIU Huaibin

doi:10.13873/J.1000-9787(2019)06-0031-04

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Method for sign language recognition based on Kinect

更新时间：2025-09-11

- Method for sign language recognition based on Kinect
- Issue 6, Pages: 31-34+38(2019)
- 作者机构：
  
  吉林大学仪器科学与电气工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2019)06-0031-04
  CLC： TP391.41
- Published：2019
- 稿件说明：
移动端阅览
QIAN Chenghui, SHAO Jingya, XIA Tao, et al. Method for sign language recognition based on Kinect[J]. 2019, (6): 31-34+38.
DOI：

QIAN Chenghui, SHAO Jingya, XIA Tao, et al. Method for sign language recognition based on Kinect[J]. 2019, (6): 31-34+38. DOI： 10.13873/J.1000-9787(2019)06-0031-04.

摘要

为实现基于Kinect的手语识别

提出了一种利用有限状态机及动态时间规整(DTW)的动态手语识别方法。首先

利用Kinect技术得到人体深度图像和骨骼特征信息;然后利用手部分割算法得到手部深度图像

再选取识别正确率高的梯度方向直方图(HOG)特征算子来提取手部特征;最后加入有限状态机和DTW算法实现动态手语识别。实验结果表明:该方法能够实现对常用手语单词、句子的识别

识别准确率可达95%。

Abstract

In order to realize sign language recognition based on Kinect

a dynamic sign language recognition method using finite state machines and dynamic time warping（ DTW） is proposed. Firstly

the Kinect technology is used to get the depth image of human body and skeleton feature information. Next

the hand depth image is obtained by using the hand segmentation algorithm. And then

the characteristics of the hand are extracted by selecting the histogram of oriented gradient（ HOG） feature operator with high accuracy of recognition. Finally

the finite state machine and DTW algorithm are added to realize dynamic sign language recognition. The experimental results show that the method can achieve the recognition of normal sign language words and sentences

and the recognition accuracy can reach up to 95 %.

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