[1]贾丙佳,李平.人机交互过程中数字手势的识别方法[J].华侨大学学报(自然科学版),2020,41(2):260-267.[doi:10.11830/ISSN.1000-5013.201906026]
　JIA Bingjia,LI Ping.Recognition Method of Digital Gestures in Human-Computer Interaction[J].Journal of Huaqiao University(Natural Science),2020,41(2):260-267.[doi:10.11830/ISSN.1000-5013.201906026]
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人机交互过程中数字手势的识别方法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第41卷
期数:
2020年第2期
页码:
260-267
栏目:
出版日期:
2020-03-20

文章信息/Info

Title:
Recognition Method of Digital Gestures in Human-Computer Interaction
文章编号:
1000-5013(2020)02-0260-08
作者:
贾丙佳;  李平
华侨大学 信息科学与工程学院, 福建 厦门 361021
Author(s):
JIA Bingjia;  LI Ping
College of Information Science and Engineering, Huaqiao University, Xiamen 361021, China
关键词:
人机交互;  Kinect;  手势识别;  深度信息;  掌心圆
Keywords:
human-computer interaction;  Kinect;  gesture recognition;  depth information;  palm circle
分类号:
TP391.4
DOI:
10.11830/ISSN.1000-5013.201906026
文献标志码:
A
摘要:
为了获得简单、高效的数字手势识别方法,增加使用者舒适的体验,提出一种基于Kinect融合深度信息和骨骼信息的数字手势识别方案.首先,使用Kinect进行深度数据的采集,建立深度图像;其次,结合骨骼追踪系统,提取人体轮廓,运用深度阈值法从轮廓中分割出手部区域,并进行二维图像的重建;再次,利用手腕和手掌骨骼点准确分割出手掌区域,并运用图像形态学开运算进行处理,得到不含手指的图像,进而提取掌心坐标;最后,计算半径,确定掌心圆,采用圆的边界和手指相交次数的方式识别手指个数.实验结果表明:数字手势识别方案能够准确、高效地识别数字手势.
Abstract:
To obtain a simple and efficient digital gesture recognition method and increase the user’s comfortable experience, a digital gesture recognition scheme based on Kinect fusion depth and bone information is proposed. Firstly, the scheme uses Kinect to collect depth data and establish depth image. Secondly, the bone tracking system is used to extract the contour of the human body. The depth threshold method is used to segment the hand region from the contour and reconstructing the two-dimensional image. Next, the skeleton points of wrist and palm are used to segment the palm area accurately, and use morphological opening operation to obtain the image without the finger, further extract the palm coordinates. Finally, the radius is calculated to determine the palm circle, the number of fingers was judged by the times the circle boundary intersected with the fingers. The experimental results show that the digital gesture recognition scheme based on Kinect fusion depth and bone information can recognize digital gestures accurately and efficiently.

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相似文献/References:

[1]张国亮,王展妮,王田.应用计算机视觉的动态手势识别综述[J].华侨大学学报(自然科学版),2014,35(6):653.[doi:10.11830/ISSN.1000-5013.2014.06.0653]
　ZHANG Guo-liang,WANG Zhan-ni,WANG Tian.Survey on Dynamic Hand Gesture Recognition with Computer Vision[J].Journal of Huaqiao University(Natural Science),2014,35(2):653.[doi:10.11830/ISSN.1000-5013.2014.06.0653]

备注/Memo

备注/Memo:
收稿日期: 2019-06-21
通信作者: 李平(1981-),女,副教授,博士,主要从事智能控制、非线性系统等的研究.E-mail:pingping_1213@126.com.
基金项目: 国家自然科学基金资助项目(61603144); 福建省自然科学基金资助项目(2018J01095); 福建省高校产学研合作科技重大项目(2013H6016); 华侨大学中青年教师科技创新资助计划项目(ZQN-PY509)
更新日期/Last Update: 2020-03-20