Characters identification in TV series

This work aims to realize a recognition system for a software engine that will automatically generate a quiz starting from a video content and reinsert it into the video, turning thus any available foreign-language video (such as news or TV series) into a remarkable learning tool. Our system includes a face tracking application which integrates the eigen face method with a temporal tracking approach. The main part of our work is to detect and identify faces from movies and to associate specific quizzes for each recognized character. The proposed approach allows to label the detected faces and maintains face tracking along the video stream. This task is challenging since characters present significant variation in their appearance. Therefore, we employed eigen faces to reconstruct the original image from training models and we developed a new technique based on frames buffering for continuous tracking in unfavorable environment conditions. Many tests were conducted and proved that our system is able to identify multiple characters. The obtained results showed the performance and the effectiveness of the proposed method.