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Performance Assessment of Face Recognition Using Super-Resolution

Published

Author(s)

Shuowen Hu, Robert Maschal, S. S. Young, Tsai H. Hong, P. Jonathon Phillips

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 reconstruction can form a higher resolution image, aiding the face recognition stage for improved performance. In this work, gallery sets and probe sets from the video database of moving faces and people [1] are used to assess the performance improvement of face recognition using super-resolution.
Proceedings Title
Proceedings of the 2010 Performance Metrics for Intelligent Systems (PerMIS) Workshop
Conference Dates
September 28-30, 2010
Conference Location
Baltimore, MD, US

Keywords

Super-resolution, face recognition, image enhancement, video surveillance

Citation

Hu, S. , Maschal, R. , Young, S. , Hong, T. and Phillips, P. (2010), Performance Assessment of Face Recognition Using Super-Resolution, Proceedings of the 2010 Performance Metrics for Intelligent Systems (PerMIS) Workshop, Baltimore, MD, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=906932 (Accessed February 26, 2024)
Created October 24, 2010, Updated October 12, 2021