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.

[1]  Ivan Laptev,et al.  Improving bag-of-features action recognition with non-local cues , 2010, BMVC.

[2]  David D. Haddock and Daniel D. Polsby A Understanding Riots , 1994 .

[3]  Greg Mori,et al.  Social roles in hierarchical models for human activity recognition , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[4]  Ramon Spaaij,et al.  Sports crowd violence: An interdisciplinary synthesis , 2014 .

[5]  Simon Hallsworth,et al.  Understanding the riots , 2015 .

[6]  Bingbing Ni,et al.  Crowded Scene Analysis: A Survey , 2015, IEEE Transactions on Circuits and Systems for Video Technology.

[7]  François Brémond,et al.  Group behavior recognition with multiple cameras , 2002, Sixth IEEE Workshop on Applications of Computer Vision, 2002. (WACV 2002). Proceedings..

[8]  Nuno Vasconcelos,et al.  Anomaly Detection and Localization in Crowded Scenes , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Tal Hassner,et al.  Violent flows: Real-time detection of violent crowd behavior , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[10]  Mubarak Shah,et al.  A Lagrangian Particle Dynamics Approach for Crowd Flow Segmentation and Stability Analysis , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Richard A. Chikota,et al.  Riot in the Cities: An Analytical Symposium on the Causes and Effects , 1970 .

[12]  Aini Hussain,et al.  Detection of snatch theft based on temporal differences in motion flow field orientation histograms , 2012 .

[13]  Anthony A. Maciejewski,et al.  An agent-based simulation of the LA 1992 riots , 2006, IC-AI.

[14]  Deva Ramanan,et al.  Efficiently Scaling up Crowdsourced Video Annotation , 2012, International Journal of Computer Vision.

[15]  Weiqiang Wang,et al.  Weakly-Supervised Violence Detection in Movies with Audio and Video Based Co-training , 2009, PCM.

[16]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[17]  Cordelia Schmid,et al.  Action recognition by dense trajectories , 2011, CVPR 2011.

[18]  Charless C. Fowlkes,et al.  Globally-optimal greedy algorithms for tracking a variable number of objects , 2011, CVPR 2011.

[19]  Peter Lacko,et al.  Riot simulation in urban areas , 2013, 2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI).

[20]  Ting Yu,et al.  Group Level Activity Recognition in Crowded Environments across Multiple Cameras , 2010, 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance.

[21]  Robert T. Collins,et al.  Multi-target Tracking by Lagrangian Relaxation to Min-cost Network Flow , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[22]  Cordelia Schmid,et al.  Learning realistic human actions from movies , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[23]  Cordelia Schmid,et al.  Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[24]  Rogério Schmidt Feris,et al.  Robust Detection of Abandoned and Removed Objects in Complex Surveillance Videos , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[25]  Silvio Savarese,et al.  What are they doing? : Collective activity classification using spatio-temporal relationship among people , 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

[26]  RamananDeva,et al.  Efficiently Scaling up Crowdsourced Video Annotation , 2013 .

[27]  Mubarak Shah,et al.  Abnormal crowd behavior detection using social force model , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.