Abstract
Face recognition is a challenging task, especially when low-resolution images or image sequences are used. A decrease in image resolution results in a loss of facial high frequency components leading to a decrease in recognition rates. In this paper, we propose a new method for super-resolution by building a dictionary of high-frequency components in the facial data, which are added to a low-resolution input image to create a super-resolved image. Our method is different from existing methods as we estimate the high-frequency components, rather than studying the direct relationship between the high- and low-resolution images. Quantitative and qualitative results are reported for both synthetic and surveillance facial image databases.
Original language | English (US) |
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DOIs | |
State | Published - 2011 |
Event | 2011 22nd British Machine Vision Conference, BMVC 2011 - Dundee, United Kingdom Duration: Aug 29 2011 → Sep 2 2011 |
Conference
Conference | 2011 22nd British Machine Vision Conference, BMVC 2011 |
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Country/Territory | United Kingdom |
City | Dundee |
Period | 8/29/11 → 9/2/11 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition