Crowd counting a la Bourdieu Automated estimation of the number of people

被引:1
|
作者
Przybylek, Karolina [1 ]
Shkroba, Illia [2 ]
机构
[1] Univ Warsaw, Podchorazych 20, PL-00721 Warsaw, Poland
[2] Polish Japanese Acad Comp Technol, Koszykowa 86, PL-02008 Warsaw, Poland
关键词
crowd counting; deep learning; mall dataset; habitus;
D O I
10.2298/CSIS200115029P
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, sociologists have taught us how important and emergent the problem of crowd counting is. They have recognised a variety of reasons for this fact, including: public safety (e.g. crushing between people, trampling underfoot, risk of spreading infectious disease, aggression), politics (e.g. police and government tend to underestimate the number of people, whilst protest organisers tend to overestimate it) and journalism (e.g. accuracy of the estimation of the ground truth supporting an article). The aim of this paper is to investigate models for crowd counting that are inspired by the observations of famous sociologist Pierre Bourdieu. We show that despite the simplicity of the models, we can achieve competitive result. This makes them suitable for low computational power and energy efficient architectures.
引用
收藏
页码:959 / 982
页数:24
相关论文
共 50 条
  • [1] Crowd Counting a la Bourdieu Automated Estimation of the Number of People
    Przybylek, Karolina
    Shkroba, Illia
    [J]. NEW TRENDS IN DATABASES AND INFORMATION SYSTEMS, ADBIS 2019, 2019, 1064 : 295 - 305
  • [2] Survey on algorithms of people counting in dense crowd and crowd density estimation
    Yang, Ge
    Zhu, Dian
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (09) : 13637 - 13648
  • [3] Survey on algorithms of people counting in dense crowd and crowd density estimation
    Ge Yang
    Dian Zhu
    [J]. Multimedia Tools and Applications, 2023, 82 : 13637 - 13648
  • [4] Estimating the Density of the People and counting the number of People in a Crowd Environment for Human Safety
    Karpagavalli, P.
    Ramprasad, A. V.
    [J]. 2013 INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND SIGNAL PROCESSING (ICCSP), 2013, : 663 - 667
  • [5] Automated Raspberry Pi Controlled People Counting System for Pilgrim Crowd Management
    Satyanarayana, P.
    Priya, K. Sai
    Chandu, M. V. Sai
    Sahithi, M.
    [J]. ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY COMPUTATIONS IN ENGINEERING SYSTEMS, ICAIECES 2017, 2018, 668 : 423 - 431
  • [6] Approaches on crowd counting and density estimation: a review
    Bo Li
    Hongbo Huang
    Ang Zhang
    Peiwen Liu
    Cheng Liu
    [J]. Pattern Analysis and Applications, 2021, 24 : 853 - 874
  • [7] Approaches on crowd counting and density estimation: a review
    Li, Bo
    Huang, Hongbo
    Zhang, Ang
    Liu, Peiwen
    Liu, Cheng
    [J]. PATTERN ANALYSIS AND APPLICATIONS, 2021, 24 (03) : 853 - 874
  • [8] Practical Automated Video Analytics for Crowd Monitoring and Counting
    Cheong, Kang Hao
    Poeschmann, Sandra
    Lai, Joel Weijia
    Koh, Jin Ming
    Acharya, U. Rajendra
    Yu, Simon Ching Man
    Tang, Kenneth Jian Wei
    [J]. IEEE ACCESS, 2019, 7 : 183252 - 183261
  • [9] A crowd counting method via density map and counting residual estimation
    Li Yang
    Yanqun Guo
    Jun Sang
    Weiqun Wu
    Zhongyuan Wu
    Qi Liu
    Xiaofeng Xia
    [J]. Multimedia Tools and Applications, 2022, 81 : 43503 - 43512
  • [10] A crowd counting method via density map and counting residual estimation
    Yang, Li
    Guo, Yanqun
    Sang, Jun
    Wu, Weiqun
    Wu, Zhongyuan
    Liu, Qi
    Xia, Xiaofeng
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (30) : 43503 - 43512