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Hajj pilgrimage video analytics using CNN
- Source :
- Bulletin of Electrical Engineering and Informatics. 10:2598-2606
- Publication Year :
- 2021
- Publisher :
- Institute of Advanced Engineering and Science, 2021.
-
Abstract
- This paper advances video analytics with a focus on crowd analysis for Hajj and Umrah pilgrimages. In recent years, there has been an increased interest in the advancement of video analytics and visible surveillance to improve the safety and security of pilgrims during their stay in Makkah. It is mainly because Hajj is an entirely special event that involve hundreds of thousands of people being clustered in a small area. This paper proposed a convolutional neural network (CNN) system for performing multitude analysis, in particular for crowd counting. In addition, it also proposes a new algorithm for applications in Hajj and Umrah. We create a new dataset based on the Hajj pilgrimage scenario in order to address this challenge. The proposed algorithm outperforms the state-of-the-art approach with a significant reduction of the mean absolute error (MAE) result: 240.0 (177.5 improvement) and the mean square error (MSE) result: 260.5 (280.1 improvement) when used with the latest dataset (HAJJ-Crowd dataset). We present density map and prediction of traditional approach in our novel HAJJ-crowd dataset for the purpose of evaluation with our proposed method.
- Subjects :
- Control and Optimization
Hajj pilgrimage
Mean squared error
Computer Networks and Communications
Computer science
business.industry
Event (computing)
Crowd analysis
Machine learning
computer.software_genre
Convolutional neural network
CNN
Crowd counting
Density estimation
Visual surveillance
Reduction (complexity)
Hardware and Architecture
Control and Systems Engineering
Analytics
Computer Science (miscellaneous)
Hajj
Artificial intelligence
Electrical and Electronic Engineering
business
Instrumentation
computer
Information Systems
Subjects
Details
- ISSN :
- 23029285 and 20893191
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- Bulletin of Electrical Engineering and Informatics
- Accession number :
- edsair.doi.dedup.....6d3d2d1685e3d2a62fcad43d311386ff