Violent flows: Real-time detection of violent crowd behavior
Open University of Israel · Weizmann Institute of Science
Abstract
Although surveillance video cameras are now widely used, their effectiveness is questionable. Here, we focus on the challenging task of monitoring crowded events for outbreaks of violence. Such scenes require a human surveyor to monitor multiple video screens, presenting crowds of people in a constantly changing sea of activity, and to identify signs of breaking violence early enough to alert help. With this in mind, we propose the following contributions: (1) We describe a novel approach to real-time detection of breaking violence in crowded scenes. Our method considers statistics of how flow-vector magnitudes change over time. These statistics, collected for short frame sequences, are represented using the…
Citation impact
- FWCI
- 16.36
- Percentile
- 100%
- References
- 37
Authors
3Topics & keywords
- Crowds
- Computer science
- Artificial intelligence
- Support vector machine
- Task (project management)
- Frame (networking)
- Computer vision
- Computer security