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  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
Pub Type: Conferences
Super-resolution, face recognition, image enhancement, video surveillance