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titleAutomatic Eye Detection and Its Validation
authorsPeng Wang, Matthew B. Green, Qiang Ji, James Wayman
keywordsface alignment, face recognition, eye detection, eye position, FRGC
abstractThe accuracy of face alignment affects the performance of
a face recognition system. Since face alignment is usually
conducted using eye positions, an accurate eye localization
algorithm is therefore essential for accurate face recognition.
In this paper, we first study the impact of eye locations on face recognition accuracy, and then introduce an automatic technique for eye detection. The performance of our automatic eye detection technique is subsequently validated using FRGC 1.0 database. The validation shows that our eye detector has an overall 94.5% eye detection rate, with the detected eyes very close to the manually provided eye positions. In addition, the face recognition performance based on the automatic eye detection is shown to be comparable to that of using manually given eye positions.
typeWorkshop Paper
journalIEEE Workshop on Face Recognition Grand Challenge Experiments (with CVPR)
published year2005
(Total records:1429)
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