Towards Intelligent Crowd Monitoring during Hajj: A Novel Dataset for Density Estimation and Anomaly Detection in the Tawaf Area (2015-2019)

This paper presents two novel datasets, Hajj-Crowd-2021, focused on crowd density and crowd anomalies during the Hajj pilgrimage. The datasets are derived from videos and images captured during the 2015-2019 Hajj and Umrah seasons, specifically in the Tawaf area surrounding the Kaaba. The crowd density dataset contains 30,000 images classified into five categories: very low, low, medium, high, and very high. The crowd anomaly dataset consists of 200 videos (100 normal and 100 anomalous) with a total of 60,000 frames. The datasets aim to address the lack of comprehensive and specific data for analyzing crowd behaviors during Hajj and Umrah. The paper describes the data collection and annotation process, as well as a comparison with existing state-of-the-art datasets. These datasets have the potential to support the development of crowd monitoring and management systems for large-scale religious gatherings.