CNN trained on practical surveilance targets.

A stationary surveilance camera is position opposite the exit to a busy station its goal is to locate and track individuals matching a target group and behaving suspicously.

Each individual is given the task of leaving the station carrying a concealed item without being seen by a a set of cameras placed throughout the station.

Using an advanced form of deep learning a Convolutional Neural Network dynamically picks out those from the group who are trying to evade detection.

The group is instructed not to act in anyway to betray their location to surveilance.

The CNN correclty identify's isolates and tracks each individual using advance image processing and deep learning.

The algorithm first works by reading the body language of any individual moving differently to the other members of the public. It then uses a rule of thumb based on its previous training to determine whether they are a valid target.

Using a purpose built database it then matches the individual using rudimentary face recognition.

Source : Reuters