Smart home based on kinect gesture recognition technology

被引：0
|
作者：
Peng, Yanfei [1 ]
Peng, Jianjun [1 ]
Li, Jiping [2 ]
Yao, Chunlong [1 ]
Shi, Xiuying [1 ]
机构：
[1] School of Information Science and Engineering, Dalian Polytechnic University, Dalian,116034, China
[2] College of Mathematics and Informatics, South China Agricultural University, Guangzhou,510642, China
来源：
International Journal of Performability Engineering | 2019年 / 15卷 / 01期
关键词：
Intelligent buildings - Gesture recognition - Automation - Health;
D O I：
10.23940/ijpe.19.01.p26.261269
中图分类号：
学科分类号：
摘要：
In order to satisfy the needs of people's intelligent home environment, this paper proposes an intelligent home control system based on gesture recognition technology. To obtain and recognize gestures of human by the depth data, skeleton data and 3D point clouds uses Kinect. The Arduino microprocessor is used to process the received data to realize the intelligent control of home appliances. The body mass index BMI was generated by the acquired biological characteristics, and detects the user's physical condition. The experimental results show that the system can achieve effective control of household appliances and accurately measure human biological characteristics by receiving and recognizing human body posture. It proves that the system is innovative and practical. © 2019 Totem Publisher, Inc. All rights reserved.
引用
收藏
页码：261 / 269
相关论文
共 50 条
  • [21] Semantic Matchmaking for Kinect-Based Posture and Gesture Recognition
    Ruta, Michele
    Scioscia, Floriano
    Di Summa, Maria
    Ieva, Saverio
    Di Sciascio, Eugenio
    Sacco, Marco
    [J]. INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING, 2014, 8 (04) : 491 - 514
  • [22] Design and Implementation of Number Gesture Recognition System Based on Kinect
    He, Xingxiu
    Zhang, Jia
    [J]. PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE, 2020, : 6329 - 6333
  • [23] Sparse Representation for Kinect Based Hand Gesture Recognition System
    Xu, Zeke
    Huang, Zhenhao
    Zhao, Zhuoxiong
    Li, Zhiyuan
    Huang, Pengsen
    [J]. PROCEEDINGS OF THE 2013 INTERNATIONAL CONFERENCE ON ADVANCED ICT AND EDUCATION, 2013, 33 : 627 - 632
  • [24] Semantic matchmaking for Kinect-based posture and gesture recognition
    Ruta, Michele
    Scioscia, Floriano
    di Summa, Maria
    Ieva, Saverio
    Di Sciascio, Eugenio
    Sacco, Marco
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC), 2014, : 15 - 22
  • [25] Authentication Based on a Changeable Biometric using Gesture Recognition with the Kinect™
    Ducray, Benoit
    Cobourne, Sheila
    Mayes, Keith
    Markantonakis, Konstantinos
    [J]. 2015 INTERNATIONAL CONFERENCE ON BIOMETRICS (ICB), 2015, : 38 - 45
  • [26] A robot control system based on gesture recognition using Kinect
    [J]. Ma, B. (mabiaoeddy@gmail.com), 2013, Universitas Ahmad Dahlan (11):
  • [27] REVIEW ON MICROSOFT KINECT'S GESTURE TECHNOLOGY BASED ROBOTICS
    Manoharan, Praveen
    Sundararaj, Nithin
    Sankar, Udhaya
    Fathima, S. J. Syed Ali
    [J]. 2017 INTERNATIONAL CONFERENCE ON INNOVATIONS IN INFORMATION, EMBEDDED AND COMMUNICATION SYSTEMS (ICIIECS), 2017,
  • [28] Multimodal Fusion-GMM based Gesture Recognition for Smart Home by WiFi Sensing
    Ding, Jianyang
    Wang, Yong
    Si, Hongyan
    Ma, Jiannan
    He, Jingwen
    Liang, Kai
    Fu, Shaozhong
    [J]. 2022 IEEE 95TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2022-SPRING), 2022,
  • [29] A Dynamic Gesture Recognition Interface for Smart Home Control based on Croatian Sign Language
    Kraljevic, Luka
    Russo, Mladen
    Paukovic, Matija
    Saric, Matko
    [J]. APPLIED SCIENCES-BASEL, 2020, 10 (07):
  • [30] Hand Gesture Recognition Based on Depth Image Using Kinect Sensor
    Truong Quang Vinh
    Nguyen Trong Tri
    [J]. PROCEEDINGS OF 2015 2ND NATIONAL FOUNDATION FOR SCIENCE AND TECHNOLOGY DEVELOPMENT CONFERENCE ON INFORMATION AND COMPUTER SCIENCE NICS 2015, 2015, : 34 - 39
12345