Detecting riots using action localization

Mass gatherings to protest or demonstrate can sometimes turn violent and take the shape of a riot. It has been observed that generally demonstrations deteriorate to riots after instigation by perpetrators. Therefore, identification of instigator(s) can prevent people from turning into a mob and help law enforcement agencies to keep them under control. To the best of our knowledge there has been no work in computer vision that automatically detects a riot like activity or its instigator. In this paper, we attempt to detect riots and identify the instigator(s). We make use of the patterns extracted from the field of sociology and collective behavior, and handle some of the common cases. We have also collected a dataset for evaluation of our algorithm, which includes videos from both actual riots, as well as acted scenarios.