Deep Learning Based Video Analytics For Person Tracking

As the assets of people are growing, security and surveillance have become a matter of great concern today. When a criminal activity takes place, the role of the witness plays a major role in nabbing the criminal. The witness usually states the gender of the criminal, the pattern of the criminal's dress, facial features of the criminal, etc. Based on the identification marks provided by the witness, the criminal is searched for in the surveillance cameras. Surveillance cameras are ubiquitous and finding criminals from a huge volume of surveillance video frames is a tedious process. In order to automate the search process, proposed a novel smart methodology using deep learning. This method takes gender, shirt pattern, and spectacle status as input to find out the object as person from the video log. The performance of this method achieves an accuracy of 87% in identifying the person in the video frame.