Performance assessment of face recognition using super-resolution

Authors:
Shuowen Hu;Tsai Hong Hong;Robert Maschal;Jonathon P. Phillips;S. Susan Young
Affiliations:
U.S. Army Research Laboratory, Adelphi, MD;NIST, Gaithersburg, MD;U.S. Army Research Laboratory, Adelphi, MD;NIST, Gaithersburg, MD;U.S. Army Research Laboratory, Adelphi, MD
Venue:
Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop
Year:
2010

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Abstract

Recognition rate of face recognition algorithms is dependent on the resolution of the imagery, specifically the number of pixels contained within the face. Using a sequence of frames from low-resolution videos, super-resolution image reconstruction can form a higher resolution image, aiding the face recognition stage for improved performance. In this work, images from a video database of moving faces and people are used to assess the performance improvement of face recognition using super-resolution.