Systematic evaluation of face detection algorithms on news videos
People are the most important subjects in news videos and for proper retrieval of people images; face detection is a very crucial step. However, face detection and recognition in news videos is a very challenging task due to the huge irregularities and high noise level in the data. In addition to that, with different face detection algorithms, the number and the type of the faces may differ. In this study, in order to get the best performance from existing methods, systematic evaluation of these methods is performed. In the experiments, news videos from TRECVID 2006 data set are used and for evaluation four different face detection methods are chosen.