HUMAN ACTIVITY RECOGNITION BASED ON EVOLVING FUZZY SYSTEMS

被引:51
|
作者
Antonio Iglesias, Jose [1 ]
Angelov, Plamen [2 ]
Ledezma, Agapito [1 ]
Sanchis, Araceli [1 ]
机构
[1] Univ Carlos III Madrid, Madrid 28914, Spain
[2] Univ Lancaster, InfoLab21, Lancaster LA1 4WA, England
基金
英国工程与自然科学研究理事会;
关键词
Activity recognition; evolving fuzzy systems; Fuzzy-Rule-Based (FRB) classifiers; DELAYED NEURAL-NETWORKS; CLASSIFICATION; MODEL; SYNCHRONIZATION; IMPROVEMENT; STABILITY;
D O I
10.1142/S0129065710002462
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Environments equipped with intelligent sensors can be of much help if they can recognize the actions or activities of their users. If this activity recognition is done automatically, it can be very useful for different tasks such as future action prediction, remote health monitoring, or interventions. Although there are several approaches for recognizing activities, most of them do not consider the changes in how a human performs a specific activity. We present an automated approach to recognize daily activities from the sensor readings of an intelligent home environment. However, as the way to perform an activity is usually not fixed but it changes and evolves, we propose an activity recognition method based on Evolving Fuzzy Systems.
引用
收藏
页码:355 / 364
页数:10
相关论文
共 50 条
  • [1] Real-Time Human Activity Recognition from Wireless Sensors using Evolving Fuzzy Systems
    Andreu, Javier
    Angelov, Plamen
    2010 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2010), 2010,
  • [2] An evolving machine learning method for human activity recognition systems
    Javier Andreu
    Plamen Angelov
    Journal of Ambient Intelligence and Humanized Computing, 2013, 4 : 195 - 206
  • [3] An evolving machine learning method for human activity recognition systems
    Andreu, Javier
    Angelov, Plamen
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2013, 4 (02) : 195 - 206
  • [4] Fuzzy Rule Inference Based Human Activity Recognition
    Chang, Jyh-Yeong
    Shyu, Jia-Jye
    Cho, Chien-Wen
    2009 IEEE CONTROL APPLICATIONS CCA & INTELLIGENT CONTROL (ISIC), VOLS 1-3, 2009, : 211 - 215
  • [5] Training-Free Fuzzy Logic Based Human Activity Recognition
    Kim, Eunju
    Helal, Sumi
    JOURNAL OF INFORMATION PROCESSING SYSTEMS, 2014, 10 (03): : 335 - 354
  • [6] Fuzzy Logic Based Human Activity Recognition in Video Surveillance Applications
    Abdelhedi, Slim
    Wali, Ali
    Alimi, Adel M.
    PROCEEDINGS OF THE SECOND INTERNATIONAL AFRO-EUROPEAN CONFERENCE FOR INDUSTRIAL ADVANCEMENT (AECIA 2015), 2016, 427 : 227 - 235
  • [7] Visualization of evolving fuzzy rule-based systems
    Henzgen, Sascha
    Strickert, Marc
    Hullermeier, Eyke
    EVOLVING SYSTEMS, 2014, 5 (03) : 175 - 191
  • [8] Stability of Evolving Fuzzy Systems Based on Data Clouds
    Rong, Hai-Jun
    Angelov, Plamen P.
    Gu, Xiaowei
    Bai, Jian-Ming
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 26 (05) : 2774 - 2784
  • [9] Exploring Methods and Systems for Vision Based Human Activity Recognition
    Amirbandi, Eisa Jafari
    Shamsipour, Ghazal
    2016 1ST CONFERENCE ON SWARM INTELLIGENCE AND EVOLUTIONARY COMPUTATION (CSIEC 2016), 2016, : 160 - 164
  • [10] Human Activity Recognition in Intelligent Home Environments: An Evolving Approach
    Antonio Iglesias, Jose
    Angelov, Plamen
    Ledezma, Agapito
    Sanchis, Araceli
    ECAI 2010 - 19TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2010, 215 : 1047 - +