DocumentCode
2861810
Title
Automatic Eye Detection and Its Validation
Author
Wang, Peng ; Green, Matthew B. ; Ji, Qiang ; Wayman, James
Author_Institution
Rensselaer Polytechnic Institute
fYear
2005
fDate
25-25 June 2005
Firstpage
164
Lastpage
164
Abstract
The 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.
Keywords
Computer errors; Databases; Detectors; Eyes; Face detection; Face recognition; Pixel; Principal component analysis; Robustness; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition - Workshops, 2005. CVPR Workshops. IEEE Computer Society Conference on
Conference_Location
San Diego, CA, USA
ISSN
1063-6919
Print_ISBN
0-7695-2372-2
Type
conf
DOI
10.1109/CVPR.2005.570
Filename
1565482
Link To Document