Sensor-based human activity recognition is an essential task for automatic behavior analysis
for sports player, senior citizens, and IoT applications. The traditional approaches are based …

Hajj, the annual pilgrimage to Makkah, is one of the most massive gathering events in the
world. It is a mandatory religious activity, once in a lifetime for every sane well-off Muslim …

This research enhances crowd analysis by focusing on excessive crowd analysis and crowd
density predictions for Hajj and Umrah pilgrimages. Crowd analysis usually analyzes the …

Predicting pedestrian trajectory is useful in many applications, such as autonomous driving
and unmanned vehicles. However, it is a challenging task because of the complexity of the …

We propose a novel method for crowd video classification, based on a two-stream
convolutional architecture which incorporates spatial and temporal networks. Our proposed …

In high-density gatherings, crowd disasters frequently occur despite all the safety measures.
Timely detection of congestion in human crowds using automated analysis of video footage …

Forecasting crowd congestion is a critical aspect of crowd management, particularly in
dynamic and densely populated areas, such as urban centers, events, or pilgrimage sites. In …

Variational based problems are an important class of problems and have a space of
improvement in image processing. Boosting techniques have been shown capable of …

Crowd density estimation is an important task for crowd monitoring. Many efforts have been
done to automate the process of estimating crowd density from images and videos. Despite …

Crowd behavior understanding is recognized as a complex problem due to unpredictable
behavior of humans and complex interactions of individuals in groups. For crowd managers …