Efficient Dense Crowd Trajectory Prediction Via Dynamic Clustering
The method groups individuals into dynamic clusters based on similar attributes over time to efficiently predict dense crowd movements. By summarizing individuals into groups, the system achieves faster processing and lower memory usage while maintaining high prediction accuracy compared to existing state-of-the-art methods.