1 research outputs found
Video face recognition via combination of realātime local features and temporalāspatial cues
Videoābased face recognition has attracted much attention and made great progress in the past decade. However, it still encounters two main problems, which are efficiently representing faces in frames and sufficiently exploiting temporalāspatial constraints between frames. The authors investigate the existing realātime features for face description, and compare their performance. Moreover, a novel approach is proposed to model temporalāspatial information which is then combined with realātime features to further enforce the consistent constraints between frames to improve the recognition performance. The experiments are validated on three video face databases and the results demonstrate that temporalāspatial cues combined with the most powerful realātime features largely improve the recognition rate