Crowds occur in a variety of situations, for instance, concerts, political speeches, rallies, marathons, and in stadiums. Crowd counting or Density Estimation helps in the management of crowds for safety and surveillance such as the deployment of law enforcement personnel and unusual behavior detection. It is also helpful in finding the volume of commuters which can be important for the development of public transportation infrastructure. Furthermore, it can be used to gauge the political significance of rallies or protests, as conflicting estimates are often reported for the same event. And since in many cases counting through turnstiles or counting by humans is not possible or is too cumbersome, we need to resort to Computer Vision based approaches to get counting estimates for dense crowds. 
The existing datasets used in Computer Vision are low-to medium density and use temporal information in the form of videos. 

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