Crowd Event Perception Based on Spatiotemporal Weber Field

Hua Wei,Zhou Su,Sha Wei

doi:10.1155/2014/719810

Abstract

Over the past decade, a wide attention has been paid to the crowd control and management in intelligent video surveillance area. Among the tasks of automatic video-based crowd management, crowd motion modeling is recognized as one of the most critical components, since it lays a crucial foundation for numerous subsequent analyses. However, it still encounters many unsolved challenges due to occlusions among pedestrians, complicated motion patterns in crowded scenarios, and so forth. Addressing these issues, we propose a novel spatiotemporal Weber field, which integrates both appearance characteristics and stimulus of crowd motion patterns, to recognize the large-scale crowd event. On the one hand, crowd motion is recognized as variations of spatiotemporal signal, and we then measure the variation based on Weber law. The result is referred to as spatiotemporal Weber variation feature. On the other hand, motivated by the achievements in crowd dynamics that crowd motion has a close relationship with interaction force, we propose a spatiotemporal Weber force feature to exploit the stimulus of crowd behaviors. Finally, we utilize the latent Dirichlet allocation model to establish the relationship between crowd events and crowd motion patterns. Experiments on PETS2009 and UMN databases demonstrate that our proposed method outperforms the previous methods for the large-scale crowd behavior perception.

Highlights

Over the past decades, crowd phenomenon has become an important carrier of economic development and culture exchange along with the steady population growth and worldwide urbanization
We propose a Spatiotemporal Weber Variation Feature (ST-WVF) for the crowd behavior perception, which adopts the Weber law to measure the variation of the video signal
Optical flow fails to exploit the spatial characteristic of the behavior, and the performance is inferior to our proposed method. These results demonstrate that crowd behavior can be recognized effectively and accurately based on our proposed spatiotemporal Weber field, because it exploits both the appearance and driven factor of the behavior

Summary

Introduction

Crowd phenomenon has become an important carrier of economic development and culture exchange along with the steady population growth and worldwide urbanization. According to the statistics of The Guardian, there have happened more than fifteen fatal crowd accidents that resulted in high casualties within the past twenty years when people lost control during the crowded special events, for example, the stampede in the Cambodia Water Festival and the Love Parade stampede in Germany. Such terrible event is much easier to control, if we get aware of the abnormal clues and nip the tragedy in the bud before it gets serious. The perception of the large-scale crowd event has attracted the attention from technical research discipline, especially for the anomalous behaviors in the crowd activities where computer vision algorithms play a growing role

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Results

Conclusion