Video recorders record the output of each security camera. After an incident, the video footage can be used for evidence by locating a suspect or criminal for a crime. A manual scan of the video footage requires a considerable amount of manpower and time, a luxury which cannot be afforded when tracking down a person of interest (POI). An automated system is proposed in this paper which aims at finding the desired POI through the available volume of video data quickly and accurately. It is visualized to go through all the available videos and detect the POI using facial recognition. Thereafter, it would create a video montage of all the desired frames and incorporate time and location information to produce a path map followed by the POI. The proposed system reduces the human burden, human error and reduces the time taken when searching the POI manually. Validation has been performed on various video data collected by ourselves as well. The results depict that the proposed system is able to correctly identify POI with an accuracy of 86% for video data captured in a constrained environment. Videos captured by a cell phone in an unconstrained environment result in an accuracy of around 80%. Real video tested in our university campus revealed the proposed system is capable of generating tracking information for POI effectively.