Exploring Methods and Systems for Vision Based Human Activity Recognition

被引:0
|
作者
Amirbandi, Eisa Jafari [1 ]
Shamsipour, Ghazal [1 ]
机构
[1] Kharazmi Univ, Dept Comp Engn, Tehran, Iran
关键词
computer vision; human activity recognition; video tracking; motion analysis; diagnosis; tagging pictures;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
this paper provides a comprehensive survey on the recent techniques of human activity recognition. The goal of the activity recognition is to automatically analyze the ongoing events. The applications of activity recognition are manifold, ranging from visual surveillance to control and video retrieval. The task is challenging due to variations in recording settings of people, environment and scene. This paper covers all aspects of the general framework of human activity recognition and provides a detailed overview of benchmark databases and current advances in this field. Finally, future directions to work on for this application are suggested.
引用
收藏
页码:160 / 164
页数:5
相关论文
共 50 条
  • [31] A lightweight hybrid vision transformer network for radar-based human activity recognition
    Huan, Sha
    Wang, Zhaoyue
    Wang, Xiaoqiang
    Wu, Limei
    Yang, Xiaoxuan
    Huang, Hongming
    Dai, Gan E.
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [32] Modelling the Influence of Cultural Information on Vision-Based Human Home Activity Recognition
    Menicatti, Roberto
    Bruno, Barbara
    Sgorbissa, Antonio
    2017 14TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAI), 2017, : 32 - 38
  • [33] Human flow recognition using deep networks and vision methods
    Zimoch, Mateusz
    Markowska-Kaczmar, Urszula
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2021, 104
  • [34] Recent Progress in Computer-Vision-Based Human Activity Recognition and Related Areas
    Rigoll, Gerhard
    PATTERN RECOGNITION AND INFORMATION PROCESSING, PRIP 2019, 2019, 1055 : 3 - 7
  • [35] Human flow recognition using deep networks and vision methods
    Zimoch, Mateusz
    Markowska-Kaczmar, Urszula
    Engineering Applications of Artificial Intelligence, 2021, 104
  • [36] Computer Vision-based Survey on Human Activity Recognition System, Challenges and Applications
    Manaf, Abdul F.
    Singh, Sukhwinder
    ICSPC'21: 2021 3RD INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION (ICPSC), 2021, : 110 - 114
  • [37] Review on recent Computer Vision Methods for Human Action Recognition
    Muhamada, Azhee Wria
    Mohammed, Aree A.
    ADCAIJ-ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL, 2021, 10 (04): : 361 - 379
  • [38] Exploring appropriate clusters in subspace for human activity recognition
    Zhang, Huiquan
    Luo, Sha
    Yoshie, Osamu
    IEEJ Transactions on Electronics, Information and Systems, 2013, 133 (12) : 2282 - 2290
  • [39] Exploring Variability in IoT Data for Human Activity Recognition
    Sakuma, Yuiko
    Kleisarchaki, Sofia
    Gurgen, Levent
    Nishi, Hiroaki
    45TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2019), 2019, : 5312 - 5318
  • [40] Ensemble Methods for Classifying of Human Activity Recognition
    Nurhanim, Ku
    Elamvazuthi, I.
    Izhar, L. I.
    2018 IEEE 4TH INTERNATIONAL SYMPOSIUM IN ROBOTICS AND MANUFACTURING AUTOMATION (ROMA), 2018,