TITLE:
Low Resolution Face Recognition in Surveillance Systems
AUTHORS:
Xiang Xu, Wanquan Liu, Ling Li
KEYWORDS:
Face Recognition; Very Low Resolution; Surveillance Camera
JOURNAL NAME:
Journal of Computer and Communications,
Vol.2 No.2,
January
10,
2014
ABSTRACT: In surveillance systems, the captured facial images are often very small
and different from the low-resolution images down-sampled from high-resolution
facial images. They generally lead to low performance in face recognition. In
this paper, we study specific scenarios of face recognition with surveillance
cameras. Three important factors that influence face recognition performance
are investigated: type of cameras, distance between the object and camera, and
the resolution of the captured face images. Each factor is numerically investigated
and analyzed in this paper. Based on these observations, a new approach is
proposed for face recognition in real surveillance environment. For a raw video
sequence captured by a surveillance camera, image pre-processing techniques are
employed to remove the illumination variations for the enhancement of image
quality. The face images are further improved through a novel face image
super-resolution method. The proposed approach is proven to significantly
improve the performance of face recognition as demonstrated by experiments.