High Magnification and Long Distance Face Recognition: Database Acquisition, Evaluation, and Enhancement

Abstract

In this paper, we describe a face video database obtained from Long Distances and with High Magnifications, IRIS- LDHM. Both indoor and outdoor sequences are collected under uncontrolled surveillance conditions. The significance of this database lies in the fact that it is the first database to provide face images from long distances (indoor: 10 m~20 m and outdoor: 50 m~300 m). The corresponding system magnification is elevated from less than 3times to 20times for indoor and up to 375times for outdoor. The database has applications in experimentations with human identification and authentication in long range surveillance and wide area monitoring. The database will be made public to the research community for perusal towards long range face related research. Deteriorations unique to high magnification and long range face images are investigated in terms of face recognition rates. Magnification blur is proved to be an additional major degradation source, which can be alleviated via blur assessment and deblurring algorithms. Experimental results validate a relative improvement of up to 25% in recognition rates after assessment and enhancement of degradations.