Visualization of faces from surveillance videos via face hallucination

Abstract

Face hallucination can be a useful tool for visualizing a low quality face into a visually better quality, making it an attractive technology for many applications. While faces in surveillance videos are usually at very low resolution, in this paper, we propose to use face hallucination technology to visualize faces from visual surveillance systems, and develop a weighted scheme to enhance the quality of face visualization from surveillance videos. Our experiment validated that in comparison with the classic eigenspace based face hallucination, our proposed weighted face hallucination strategy can help improve the overall quality of a facial image extracted from surveillance footage.