A multi-view face database from Turkish TV series

Facial image processing and analysis has numerous applications. Recently, with deep learning based approaches, a significant performance improvement has been obtained. An important factor affecting the performance of the deep learning-based systems is availability of large amount of data. Therefore, recently, a couple of large-scale face datasets that contain still images of subjects have become publicly available. However, a video face database that contains both a large number of subjects as well as a large number of samples per subject has not been available, yet. In this study, to fulfill this need, Turkish TV series have been used, and preparation of a multi-view face sequence dataset has been focused. In the study, state-of-the-art off-the-shelf tools have been utilized for face detection, face alignment, and face recognition and the steps we have followed to collect the database are presented. Our goal is, upon completion of the processes, to reach a face database of at least 3000 subjects, each having at least 100 video sequences. In the database, along with the identity labels, we also plan to generate age and gender labels. We believe that this database would become an invaluable resource for automatic facial image processing and analysis research, especially, for the approaches that aim at exploiting dynamic features.