Crowd behaviour recognition system for evacuation support by using machine learning

被引:0
|
作者
Horii H. [1 ]
机构
[1] Kokushikan University, Setagaya Tokyo
关键词
Crowd behaviour recognition; Deep learning; Image recognition; Machine learning;
D O I
10.18280/ijsse.100211
中图分类号
学科分类号
摘要
The crowd behaviour recognition system is a subsystem of a distributed cooperative adaptive evacuation guide system, and it detects and forecasts crowd flow and anomaly occurrence by using machine learning method such as deep learning with visual and depth information obtained by RGB-D camera. The distributed cooperative adaptive evacuation guide system aims to suggest evacuation routes at extensive evacuation situations by autonomously cooperation among plural sensors and evacuation guiding devices. In this paper, a recognition method of overall behaviour of the crowd is proposed. Some indices for indicating the situation are examined in order to recognize the overall behaviour of the crowd flow and the anomaly occurrence, and cooperate among the system by sharing the recognition results rapidly. © 2020 WITPress. All rights reserved.
引用
收藏
页码:243 / 246
页数:3
相关论文
共 50 条
  • [1] A System of Clothing Boundary Recognition Using Machine Learning For Life Support Robots
    Zhao, Hanqing
    Nambo, Hidetaka
    2020 5TH INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATICS AND BIOMEDICAL SCIENCES (ICIIBMS 2020), 2020, : 1 - 7
  • [2] A review on crowd analysis of evacuation and abnormality detection based on machine learning systems
    Bahamid, Alala
    Mohd Ibrahim, Azhar
    NEURAL COMPUTING & APPLICATIONS, 2022, 34 (24): : 21641 - 21655
  • [3] A review on crowd analysis of evacuation and abnormality detection based on machine learning systems
    Alala Bahamid
    Azhar Mohd Ibrahim
    Neural Computing and Applications, 2022, 34 : 21641 - 21655
  • [4] Machine Learning Methods from Group to Crowd Behaviour Analysis
    Felipe Borja-Borja, Luis
    Saval-Calvo, Marcelo
    Azorin-Lopez, Jorge
    ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2017, PT II, 2017, 10306 : 294 - 305
  • [5] Facial Expression Recognition System Using Machine Learning
    Kim, Sanghyuk
    An, Gwon Hwan
    Kang, Suk-Ju
    PROCEEDINGS INTERNATIONAL SOC DESIGN CONFERENCE 2017 (ISOCC 2017), 2017, : 266 - 267
  • [6] SYSTEM FOR RECOGNITION OF FACIAL EXPRESSIONS USING MACHINE LEARNING
    Almeida Silva, Tharcio Thalles
    Andrade, Alexsandra Oliveira
    da Silva, Natalia Pinheiro
    2020 XVIII LATIN AMERICAN ROBOTICS SYMPOSIUM, 2020 XII BRAZILIAN SYMPOSIUM ON ROBOTICS AND 2020 XI WORKSHOP OF ROBOTICS IN EDUCATION (LARS-SBR-WRE 2020), 2020, : 162 - 167
  • [7] Epileptic Patient Activity Recognition System Using Extreme Learning Machine Method
    Ayman, Ummara
    Zia, Muhammad Sultan
    Okon, Ofonime Dominic
    Rehman, Najam-ur
    Meraj, Talha
    Ragab, Adham E.
    Rauf, Hafiz Tayyab
    BIOMEDICINES, 2023, 11 (03)
  • [8] Pilot Support System: A Machine Learning Approach
    Watkins, David
    Gallardo, Guillermo
    Chau, Savio
    2018 IEEE 12TH INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC), 2018, : 325 - 328
  • [9] Character Recognition using Machine Learning and Deep Learning - A Survey
    Sharma, Reya
    Kaushik, Baijnath
    Gondhi, Naveen
    2020 INTERNATIONAL CONFERENCE ON EMERGING SMART COMPUTING AND INFORMATICS (ESCI), 2020, : 341 - 345
  • [10] Manuscripts Character Recognition Using Machine Learning and Deep Learning
    Islam, Mohammad Anwarul
    Iacob, Ionut E.
    MODELLING, 2023, 4 (02): : 168 - 188