People Counting and Tracking for Surveillance

The computer vision community has expended a great amount of effort in recent years towards the goal of tracking people in videos. Much more recently, algorithms have been developed to track multiple people in videos robustly and in real-time. The goal of this project is to implement a system based on one of those algorithms, in order to count and track the people in a database of surveillance footage. Due to several constraints and performance issues, however, a more straightforward algorithm based on background subtraction is implemented and shows acceptable performance levels. Further improvements are considered to improve the performance, including implementations of algorithms such as BraMBLe [3].