Machine Learning-Based Crowd behavior Analysis and Forecasting

Authors

  • Sachin Bhardwaj  Assistant Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, Uttar Pradesh, India
  • Apoorva Dwivedi  Assistant Professor, Department of Computer Science & Engineering, Invertis University, Bareilly, Uttar Pradesh, India
  • Ashutosh Pandey  Assistant Professor, Department of Computer Science & Engineering, Pranveer Singh Institute of Technology (PSIT), Kanpur, Uttar Pradesh, India
  • Dr. Yusuf Perwej  Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, Uttar Pradesh, India
  • Pervez Rauf Khan  Assistant Professor & HoD, Department of Computer Science & Engineering, Azad Institute of Engineering and Technology (AIET), Lucknow, Uttar Pradesh, India

DOI:

https://doi.org/10.32628/CSEIT23903104

Keywords:

Abnormal Activity Detection, Image Pre-Processing, Crowd Analysis, Machine Learning, ShanghaiTech Dataset, Rectified Linear Unit (ReLU), Multicolumn Convolutional Neural Network (MCNN).

Abstract

In many places today, the world's overcrowding causes crowded conditions. Analysis of crowd activity is a developing field of study. It is common knowledge that mob activity can forecast what might happen during an event. Crowd management could be very effective if situations like riots, mass lynchings, traffic jams, accidents, stampedes, etc. could be predicted beforehand. In this paper, we propose a new multicolumn convolutional neural network (MCNN) based technique for predicting mob behavior. The features of the incoming image are first analyzed and extracted. The approximated number of the gathering is then established, and image cropping is completed. For each area of the image, low level characteristics are retrieved. The objects in the picture are then created as density images. Using our method, the gathered characteristics and their object density maps are then linearly mapped. At last, we forecast and quantify the population using the MCNN algorithm. For the ShanghaiTech dataset, we have evaluated our method using actual data.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-06-30

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Volume 9, Issue 3, May-June-2023

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Research Articles

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[1]
Sachin Bhardwaj, Apoorva Dwivedi, Ashutosh Pandey, Dr. Yusuf Perwej, Pervez Rauf Khan, " Machine Learning-Based Crowd behavior Analysis and Forecasting" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 3, pp.418-429, May-June-2023. Available at doi : https://doi.org/10.32628/CSEIT23903104